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Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #1
Learning Active Learning from Data
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #2
Scalable Variational Inference for Dynamical Systems
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #3
Active Learning from Peers
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #4
Gradient Episodic Memory for Continual Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #5
Consistent Multitask Learning with Nonlinear Output Relations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #6
Joint distribution optimal transportation for domain adaptation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #7
Learning Multiple Tasks with Multilinear Relationship Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #8
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #9
Matching neural paths: transfer from recognition to correspondence search
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #10
Do Deep Neural Networks Suffer from Crowding?
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #11
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #12
Neural Expectation Maximization
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #13
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #14
PRUNE: Preserving Proximity and Global Ranking for Network Embedding
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #15
Unsupervised Transformation Learning via Convex Relaxations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #16
Hunt For The Unique, Stable, Sparse And Fast Feature Learning On Graphs
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #17
Deep Subspace Clustering Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #18
Learning Graph Representations with Embedding Propagation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #19
Unsupervised Sequence Classification using Sequential Output Statistics
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #20
Context Selection for Embedding Models
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #21
Probabilistic Rule Realization and Selection
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #22
Trimmed Density Ratio Estimation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #23
A Minimax Optimal Algorithm for Crowdsourcing
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #24
Introspective Classification with Convolutional Nets
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #25
Adaptive Classification for Prediction Under a Budget
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #26
Learning with Feature Evolvable Streams
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #27
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #28
Adversarial Surrogate Losses for Ordinal Regression
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #29
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #30
Cost efficient gradient boosting
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #31
LightGBM: A Highly Efficient Gradient Boosting Decision Tree
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #32
Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #33
Inferring Generative Model Structure with Static Analysis
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #34
Scalable Model Selection for Belief Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #35
Time-dependent spatially varying graphical models, with application to brain fMRI data analysis
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #36
A Bayesian Data Augmentation Approach for Learning Deep Models
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #37
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #38
Deep Learning with Topological Signatures
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #39
Practical Hash Functions for Similarity Estimation and Dimensionality Reduction
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #40
Maxing and Ranking with Few Assumptions
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #41
Kernel functions based on triplet comparisons
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #42
Learning A Structured Optimal Bipartite Graph for Co-Clustering
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #43
Multi-way Interacting Regression via Factorization Machines
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #44
Maximum Margin Interval Trees
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #45
Kernel Feature Selection via Conditional Covariance Minimization
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #46
Improved Graph Laplacian via Geometric Self-Consistency
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #47
Mixture-Rank Matrix Approximation for Collaborative Filtering
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #48
Predictive State Recurrent Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #49
Hierarchical Methods of Moments
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #50
Multitask Spectral Learning of Weighted Automata
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #51
Generative Local Metric Learning for Kernel Regression
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #52
Principles of Riemannian Geometry in Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #53
Subset Selection and Summarization in Sequential Data
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #54
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #55
Fast, Sample-Efficient Algorithms for Structured Phase Retrieval
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #56
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #57
Parametric Simplex Method for Sparse Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #58
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #59
FALKON: An Optimal Large Scale Kernel Method
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #60
Recursive Sampling for the Nystrom Method
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #61
Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #62
Robust Hypothesis Test for Nonlinear Effect with Gaussian Processes
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #63
Invariance and Stability of Deep Convolutional Representations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #64
Testing and Learning on Distributions with Symmetric Noise Invariance
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #65
An Empirical Study on The Properties of Random Bases for Kernel Methods
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #66
Max-Margin Invariant Features from Transformed Unlabelled Data
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #67
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #69
The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #70
The Importance of Communities for Learning to Influence
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #71
Inductive Representation Learning on Large Graphs
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #72
A Meta-Learning Perspective on Cold-Start Recommendations for Items
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #73
DropoutNet: Addressing Cold Start in Recommender Systems
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #74
Federated Multi-Task Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #75
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #76
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #77
Tomography of the London Underground: a Scalable Model for Origin-Destination Data
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #78
Matching on Balanced Nonlinear Representations for Treatment Effects Estimation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #79
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #80
Hiding Images in Plain Sight: Deep Steganography
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #81
Universal Style Transfer via Feature Transforms
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #82
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #83
Unbounded cache model for online language modeling with open vocabulary
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #84
Deconvolutional Paragraph Representation Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #85
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #86
Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #87
Teaching Machines to Describe Images with Natural Language Feedback
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #88
High-Order Attention Models for Visual Question Answering
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #89
Visual Reference Resolution using Attention Memory for Visual Dialog
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #90
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #91
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #92
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #93
Incorporating Side Information by Adaptive Convolution
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #94
Learning a Multi-View Stereo Machine
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #95
Pose Guided Person Image Generation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #96
Working hard to know your neighbor's margins: Local descriptor learning loss
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #97
Toward Multimodal Image-to-Image Translation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #98
Deep Supervised Discrete Hashing
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #99
SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #100
Hash Embeddings for Efficient Word Representations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #101
A Regularized Framework for Sparse and Structured Neural Attention
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #102
Attentional Pooling for Action Recognition
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #103
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #104
Dilated Recurrent Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #105
Learning Hierarchical Information Flow with Recurrent Neural Modules
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #106
Wasserstein Learning of Deep Generative Point Process Models
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #107
Stabilizing Training of Generative Adversarial Networks through Regularization
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #108
Neural Variational Inference and Learning in Undirected Graphical Models
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #109
Adversarial Symmetric Variational Autoencoder
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #110
Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #111
Z-Forcing: Training Stochastic Recurrent Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #112
One-Shot Imitation Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #113
Reconstruct & Crush Network
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #114
Fader Networks:Manipulating Images by Sliding Attributes
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #115
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #116
VAIN: Attentional Multi-agent Predictive Modeling
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #117
Real Time Image Saliency for Black Box Classifiers
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #118
Prototypical Networks for Few-shot Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #119
Few-Shot Learning Through an Information Retrieval Lens
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #120
The Reversible Residual Network: Backpropagation Without Storing Activations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #121
Gated Recurrent Convolution Neural Network for OCR
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #122
Learning Efficient Object Detection Models with Knowledge Distillation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #124
Decoupling "when to update" from "how to update"
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #125
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #126
Differentiable Learning of Logical Rules for Knowledge Base Reasoning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #127
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #128
Neural Program Meta-Induction
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #129
Saliency-based Sequential Image Attention with Multiset Prediction
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #130
Protein Interface Prediction using Graph Convolutional Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #131
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #132
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #133
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #134
Selective Classification for Deep Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #135
Deep Lattice Networks and Partial Monotonic Functions
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #136
Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #137
Bayesian Compression for Deep Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #138
Lower bounds on the robustness to adversarial perturbations
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #139
Sobolev Training for Neural Networks
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #140
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #141
Population Matching Discrepancy and Applications in Deep Learning
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #142
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #143
Robust Imitation of Diverse Behaviors
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #144
Question Asking as Program Generation
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #145
Variational Laws of Visual Attention for Dynamic Scenes
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #146
Flexible statistical inference for mechanistic models of neural dynamics
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #147
Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #148
YASS: Yet Another Spike Sorter
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #149
Neural system identification for large populations separating “what” and “where”
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #150
A simple model of recognition and recall memory
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #151
Gaussian process based nonlinear latent structure discovery in multivariate spike train data
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #152
Reconstructing perceived faces from brain activations with deep adversarial neural decoding
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #153
Cross-Spectral Factor Analysis
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #154
Regularized Modal Regression with Applications in Cognitive Impairment Prediction
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Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #155
Stochastic Submodular Maximization: The Case of Coverage Functions
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Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #156
Gradient Methods for Submodular Maximization
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #157
Non-convex Finite-Sum Optimization Via SCSG Methods
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #158
Influence Maximization with $\varepsilon$-Almost Submodular Threshold Functions
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #159
Subset Selection under Noise
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #160
Polynomial time algorithms for dual volume sampling
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #161
Lookahead Bayesian Optimization with Inequality Constraints
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #162
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #163
Solving Most Systems of Random Quadratic Equations
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #164
Learning ReLUs via Gradient Descent
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #165
Stochastic Mirror Descent in Variationally Coherent Optimization Problems
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #166
Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #167
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #168
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #169
A New Alternating Direction Method for Linear Programming
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #170
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #171
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #172
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #173
Accelerated consensus via Min-Sum Splitting
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #174
Integration Methods and Optimization Algorithms
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #175
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems
In
Posters Mon
[
Paper]
[
Video Presentation]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #176
A Screening Rule for l1-Regularized Ising Model Estimation
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #177
Uprooting and Rerooting Higher-Order Graphical Models
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #178
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #179
Inference in Graphical Models via Semidefinite Programming Hierarchies
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #180
Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #181
Dynamic Importance Sampling for Anytime Bounds of the Partition Function
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #182
Nonbacktracking Bounds on the Influence in Independent Cascade Models
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #183
Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #184
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #185
Gauging Variational Inference
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #186
Variational Inference via $\chi$ Upper Bound Minimization
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #187
Collapsed variational Bayes for Markov jump processes
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #188
Bayesian Dyadic Trees and Histograms for Regression
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #189
Differentially private Bayesian learning on distributed data
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #190
Model-Powered Conditional Independence Test
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #191
When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #192
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #193
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #194
Expectation Propagation for t-Exponential Family Using q-Algebra
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #195
A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #196
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #197
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #198
Scalable Levy Process Priors for Spectral Kernel Learning
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #199
InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #200
Hybrid Reward Architecture for Reinforcement Learning
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #201
Shallow Updates for Deep Reinforcement Learning
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #202
Towards Generalization and Simplicity in Continuous Control
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #203
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #204
Scalable Planning with Tensorflow for Hybrid Nonlinear Domains
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #205
Task-based End-to-end Model Learning in Stochastic Optimization
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #206
Value Prediction Network
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #207
Variable Importance Using Decision Trees
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #208
The Expressive Power of Neural Networks: A View from the Width
In
Posters Mon
[
Paper]
[
Video Presentation]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #209
SGD Learns the Conjugate Kernel Class of the Network
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #210
Effective Parallelisation for Machine Learning
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #211
Noise-Tolerant Interactive Learning Using Pairwise Comparisons
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #212
A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #213
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #214
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #215
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #216
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity
In
Posters Mon
[
Paper]
[
Video Presentation]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #217
From which world is your graph
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #218
Mean Field Residual Networks: On the Edge of Chaos
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #219
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #220
On clustering network-valued data
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #221
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #222
AdaGAN: Boosting Generative Models
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #223
Discovering Potential Correlations via Hypercontractivity
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #224
Phase Transitions in the Pooled Data Problem
In
Posters Mon
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #225
Coded Distributed Computing for Inverse Problems
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #226
Query Complexity of Clustering with Side Information
In
Posters Mon
[
Paper]
Poster
Mon Dec 04 06:30 PM -- 10:30 PM (PST) @ Pacific Ballroom #227
Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming Network
In
Posters Mon
[
Paper]