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Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #1
Experimental Design for Cost-Aware Learning of Causal Graphs
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #2
Removing Hidden Confounding by Experimental Grounding
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #3
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #4
Structural Causal Bandits: Where to Intervene?
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #5
Uplift Modeling from Separate Labels
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #6
Causal Inference with Noisy and Missing Covariates via Matrix Factorization
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #7
Fast Estimation of Causal Interactions using Wold Processes
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Paper]
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3-Minute-Video]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #8
Learning and Testing Causal Models with Interventions
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #9
Causal Inference via Kernel Deviance Measures
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #10
Multi-domain Causal Structure Learning in Linear Systems
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #11
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #12
Direct Estimation of Differences in Causal Graphs
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #13
Identification and Estimation of Causal Effects from Dependent Data
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #14
Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #15
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #16
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #17
Distributionally Robust Graphical Models
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #18
Flexible and accurate inference and learning for deep generative models
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #19
Provable Gaussian Embedding with One Observation
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #20
Learning and Inference in Hilbert Space with Quantum Graphical Models
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #21
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #22
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #23
Theoretical guarantees for EM under misspecified Gaussian mixture models
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #24
Nonparametric learning from Bayesian models with randomized objective functions
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #26
A Bayesian Nonparametric View on Count-Min Sketch
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Paper]
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3-Minute-Video]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #27
Communication Efficient Parallel Algorithms for Optimization on Manifolds
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #29
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #30
Faithful Inversion of Generative Models for Effective Amortized Inference
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #31
A Stein variational Newton method
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #32
Reparameterization Gradient for Non-differentiable Models
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #33
Implicit Reparameterization Gradients
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #34
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #35
Wasserstein Variational Inference
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #36
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #37
Variational Inference with Tail-adaptive f-Divergence
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #38
Boosting Black Box Variational Inference
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #39
Discretely Relaxing Continuous Variables for tractable Variational Inference
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Paper]
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3-Minute-Video]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #40
Using Large Ensembles of Control Variates for Variational Inference
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #41
The promises and pitfalls of Stochastic Gradient Langevin Dynamics
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #42
Large-Scale Stochastic Sampling from the Probability Simplex
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #44
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #45
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #46
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #48
Posterior Concentration for Sparse Deep Learning
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #49
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #50
Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #51
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #52
Implicit Probabilistic Integrators for ODEs
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #53
A Bayes-Sard Cubature Method
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #54
Deep State Space Models for Time Series Forecasting
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #55
BRUNO: A Deep Recurrent Model for Exchangeable Data
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #56
Scaling Gaussian Process Regression with Derivatives
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #57
Algebraic tests of general Gaussian latent tree models
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #58
Differentially Private Bayesian Inference for Exponential Families
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #59
Semi-crowdsourced Clustering with Deep Generative Models
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #60
Deep Poisson gamma dynamical systems
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #61
Deep State Space Models for Unconditional Word Generation
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #62
Modular Networks: Learning to Decompose Neural Computation
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #63
Gaussian Process Prior Variational Autoencoders
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #64
Bayesian Semi-supervised Learning with Graph Gaussian Processes
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #65
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #66
Variational Bayesian Monte Carlo
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #67
Bayesian Alignments of Warped Multi-Output Gaussian Processes
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #68
Automating Bayesian optimization with Bayesian optimization
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #69
Infinite-Horizon Gaussian Processes
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #70
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #71
Algorithmic Linearly Constrained Gaussian Processes
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #72
Efficient Projection onto the Perfect Phylogeny Model
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #73
Distributed $k$-Clustering for Data with Heavy Noise
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #74
Communication Compression for Decentralized Training
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #75
Do Less, Get More: Streaming Submodular Maximization with Subsampling
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #76
Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #77
Provable Variational Inference for Constrained Log-Submodular Models
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #78
Fast greedy algorithms for dictionary selection with generalized sparsity constraints
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #79
Boolean Decision Rules via Column Generation
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #80
Computing Kantorovich-Wasserstein Distances on $d$-dimensional histograms using $(d+1)$-partite graphs
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #81
Adaptive Negative Curvature Descent with Applications in Non-convex Optimization
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #82
Implicit Bias of Gradient Descent on Linear Convolutional Networks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #83
Deep Generative Models for Distribution-Preserving Lossy Compression
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #84
Visual Object Networks: Image Generation with Disentangled 3D Representations
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #85
Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #86
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #87
Discrimination-aware Channel Pruning for Deep Neural Networks
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #88
Probabilistic Model-Agnostic Meta-Learning
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #89
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #90
Understanding Batch Normalization
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #91
How Many Samples are Needed to Estimate a Convolutional Neural Network?
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #92
Robust Detection of Adversarial Attacks by Modeling the Intrinsic Properties of Deep Neural Networks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #93
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #94
Automatic differentiation in ML: Where we are and where we should be going
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #95
Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #96
Toddler-Inspired Visual Object Learning
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #97
Generalisation in humans and deep neural networks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #98
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 210 #99
Incorporating Context into Language Encoding Models for fMRI
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Paper]
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3-Minute-Video]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #101
Mental Sampling in Multimodal Representations
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #102
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #103
Efficient inference for time-varying behavior during learning
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #104
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #105
Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #106
Connectionist Temporal Classification with Maximum Entropy Regularization
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #107
Removing the Feature Correlation Effect of Multiplicative Noise
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #108
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #109
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #110
Entropy and mutual information in models of deep neural networks
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Paper]
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3-Minute-Video]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #111
The committee machine: Computational to statistical gaps in learning a two-layers neural network
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #112
A Unified Framework for Extensive-Form Game Abstraction with Bounds
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #113
Connecting Optimization and Regularization Paths
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #114
Overlapping Clustering Models, and One (class) SVM to Bind Them All
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #115
Learning latent variable structured prediction models with Gaussian perturbations
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #116
Self-Supervised Generation of Spatial Audio for 360° Video
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #117
Symbolic Graph Reasoning Meets Convolutions
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #118
Towards Deep Conversational Recommendations
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Paper]
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3-Minute-Video]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #119
Human-in-the-Loop Interpretability Prior
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #120
Why Is My Classifier Discriminatory?
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #121
Link Prediction Based on Graph Neural Networks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #122
KONG: Kernels for ordered-neighborhood graphs
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #123
Efficient Stochastic Gradient Hard Thresholding
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #124
Measures of distortion for machine learning
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #125
Relating Leverage Scores and Density using Regularized Christoffel Functions
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #126
Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #127
Learning with SGD and Random Features
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #128
But How Does It Work in Theory? Linear SVM with Random Features
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #129
Statistical and Computational Trade-Offs in Kernel K-Means
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #130
Quadrature-based features for kernel approximation
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #131
Processing of missing data by neural networks
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #132
Constructing Deep Neural Networks by Bayesian Network Structure Learning
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #133
Mallows Models for Top-k Lists
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #134
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #135
Maximum-Entropy Fine Grained Classification
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #136
Efficient Loss-Based Decoding on Graphs for Extreme Classification
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #137
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #138
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #139
Deep Structured Prediction with Nonlinear Output Transformations
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #140
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #141
Large Margin Deep Networks for Classification
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #142
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #143
Multitask Boosting for Survival Analysis with Competing Risks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #144
Multi-Layered Gradient Boosting Decision Trees
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #145
Unsupervised Adversarial Invariance
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #146
Learning Deep Disentangled Embeddings With the F-Statistic Loss
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #147
Learning Latent Subspaces in Variational Autoencoders
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #148
Dual Swap Disentangling
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #149
Joint Autoregressive and Hierarchical Priors for Learned Image Compression
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #150
Group Equivariant Capsule Networks
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #151
Learning Disentangled Joint Continuous and Discrete Representations
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #152
Image-to-image translation for cross-domain disentanglement
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #154
Non-Adversarial Mapping with VAEs
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #155
Learning to Teach with Dynamic Loss Functions
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #156
Maximizing acquisition functions for Bayesian optimization
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #157
MetaReg: Towards Domain Generalization using Meta-Regularization
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #158
Transfer Learning with Neural AutoML
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #159
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #160
Lifelong Inverse Reinforcement Learning
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #161
Safe Active Learning for Time-Series Modeling with Gaussian Processes
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #162
Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #163
Preference Based Adaptation for Learning Objectives
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #164
Byzantine Stochastic Gradient Descent
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #165
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #166
Online Learning of Quantum States
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Paper]
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #167
Horizon-Independent Minimax Linear Regression
Poster
Thu Dec 06 07:45 AM -- 09:45 AM (PST) @ Room 517 AB #169
A Model for Learned Bloom Filters and Optimizing by Sandwiching