Downloads 2007
Number of events: 274
- A Bayesian Framework for Cross-Situational Word-Learning
- A Bayesian LDA-based model for semi-supervised part-of-speech tagging
- A Bayesian Model of Conditioned Perception
- A complexity measure for intuitive theories
- A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses
- A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
- Active Preference Learning with Discrete Choice Data
- Adaptive Bottle
- Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis
- Adaptive Online Gradient Descent
- A general agnostic active learning algorithm
- A General Boosting Method and its Application to Learning Ranking Functions for Web Search
- Agreement-Based Learning
- A Kernel Statistical Test of Independence
- A learning framework for nearest neighbor search
- A Multiplicative Weights Algorithm for Apprenticeship Learning
- An Analysis of Convex Relaxations for MAP Estimation
- An Analysis of Inference with the Universum
- A neural network implementing optimal state estimation based on dynamic spike train decoding
- A New View of Automatic Relevance Determination
- An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
- An online Hebbian learning rule that performs Independent Component Analysis
- Anytime Induction of Cost-sensitive Trees
- Approximate Bayesian Inference in Continuous/Hybrid Models
- A Probabilistic Approach to Language Change
- A probabilistic model for generating realistic lip movements from speech
- A Pulse Modulated Neural Integrator Implemented in aVLSI
- A Randomized Algorithm for Large Scale Support Vector Learning
- A Risk Minimization Principle for a Class of Parzen Estimators
- A Spectral Regularization Framework for Multi-Task Structure Learning
- Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
- A Unified Model for Content Based Image Suggestion and Feature Selection
- A Unified Near-Optimal Estimator For Dimension Reduction in lα (0<α≤2) Using Sta
- Automatic Cameraman
- Automatic Generation of Social Tags for Music Recommendation
- Basal-ganglia-inspired Hierarchical Reinforcement Learning in an AIBO robot
- Bayes-Adaptive POMDPs
- Bayesian Agglomerative Clustering with Coalescents
- Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms
- Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
- Bayesian Multi-View Learning
- Bayesian Policy Learning with Trans-Dimensional MCMC
- Better than least squares: comparison of objective functions for estimating linear-nonlinear models
- Beyond Simple Cells: Probabilistic Models for Visual Cortical Processing
- Blind channel identification for speech dereverberation using l1-norm sparse learning
- Boosting Algorithms for Maximizing the Soft Margin
- Boosting the Area under the ROC Curve
- Building a 3-D Model From a Single Still Image
- Bundle Methods for Machine Learning
- Catching Change-points with Lasso
- Catching Up Faster in Bayesian Model Selection and Model Averaging
- Classification via Minimum Incremental Coding Length (MICL)
- CLOP: a Matlab Learning Object Package
- Cluster Stability for Finite Samples
- COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking
- Collapsed Variational Inference for HDP
- Collective Inference on Markov Models for Modeling Bird Migration
- Colored Maximum Variance Unfolding
- Combined discriminative and generative articulated pose and non-rigid shape estimation
- Comparing Bayesian models for multisensory cue combination without mandatory integration
- Competition Adds Complexity
- Compressed Regression
- Computational and Statistical Problems in Population Genetics
- Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria
- Computing Robust Counter-Strategies
- Configuration Estimates Improve Pedestrian Finding
- Congruence between model and human attention reveals unique signatures of critical visual events
- Consistent Minimization of Clustering Objective Functions
- Continuous Time Particle Filtering for fMRI
- Contraction of VLSI Spiking Neurons
- Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons
- Convex Clustering with Exemplar-Based Models
- Convex Learning with Invariances
- Convex Relaxations of EM
- Cooled and Relaxed Survey Propagation for MRFs
- Core Knowledge of Number and Geometry
- CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation
- Deep Belief Nets
- Demonstrations
- Demonstrations
- Density Estimation under Independent Similarly Distributed Sampling Assumptions
- DIFFRAC: a discriminative and flexible framework for clustering
- Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
- Discovering Weakly-Interacting Factors in a Complex Stochastic Process
- Discriminative Batch Mode Active Learning
- Discriminative Keyword Selection Using Support Vector Machines
- Discriminative K-means for Clustering
- Discriminative Log-Linear Grammars with Latent Variables
- Distributed Inference for Latent Dirichlet Allocation
- EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection
- Efficient Bayesian Inference for Dynamically Changing Graphs
- Efficient Convex Relaxation for Transductive Support Vector Machine
- Efficient Inference forDistributions on Permutations
- Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 1)
- Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 2)
- Efficient multiple hyperparameter learning for log-linear models
- Efficient Principled Learning of Thin Junction Trees
- Elefant
- Ensemble Clustering using Semidefinite Programming
- Estimating disparity with confidence from energy neurons
- Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization
- Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks
- Expectation Maximization, Posterior Constraints, and Statistical Alignment
- Experience-Guided Search: A Theory of Attentional Control
- Exponential Family Predictive Representations of State
- Extending position/phase-shift tuning to motion energy neurons improves velocity discrimination
- Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
- Fast Variational Inference for Large-scale Internet Diagnosis
- FilterBoost: Regression and Classification on Large Datasets
- Fitted Q-iteration in continuous action-space MDPs
- Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations
- Gaussian Process Models for Link Analysis and Transfer Learning
- Gender and Age Recognition
- Graphical models for HIV vaccine design and genome-wide association studies
- GRIFT: A graphical model for inferring visual classification features from human data
- Heterogeneous Component Analysis
- Hidden Common Cause Relations in Relational Learning
- Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion
- Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 1)
- Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 2)
- Hierarchical Penalization
- Hippocampal Contributions to Control: The Third Way
- HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
- Holistic Scene Understanding from Visual and Range Data
- How SVMs can estimate quantiles and the median
- Human Computation
- IBM Student Reception
- Incremental Natural Actor-Critic Algorithms
- Inferring Elapsed Time from Stochastic Neural Processes
- Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
- Infinite State Bayes-Nets for Structured Domains
- Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
- Iterative Non-linear Dimensionality Reduction with Manifold Sculpting
- Kernel Measures of Conditional Dependence
- Kernels on Attributed Pointsets with Applications
- Large Scale Brain Dynamics (Part 1)
- Large Scale Brain Dynamics (Part 2)
- Learning Bounds for Domain Adaptation
- Learning Horizontal Connections in a Sparse Coding Model of Natural Images
- Learning Monotonic Transformations for Classification
- Learning the 2-D Topology of Images
- Learning the structure of manifolds using random projections
- Learning to classify complex patterns using a VLSI network of spiking neurons
- Learning To Race by Model-Based Reinforcement Learning with Adaptive Abstraction
- Learning Using Many Examples
- Learning Visual Attributes
- Learning with Transformation Invariant Kernels
- Learning with Tree-Averaged Densities and Distributions
- Linear programming analysis of loopy belief propagation for weighted matching
- Local Algorithms for Approximate Inference in Minor-Excluded Graphs
- Locality and low-dimensions in the prediction of natural experience from fMRI
- Loop Series and Bethe Variational Bounds in Attractive Graphical Models
- Machine Learning and Games (MALAGA): Open Directions in Applying Machine Learning to Games
- Machine Learning for Systems Problems (Part 1)
- Machine Learning for Systems Problems (Part 2)
- Machine Learning for Web Search
- Machine Learning in Adversarial Environments for Computer Security
- Machine Learning in Computational Biology (Part 1)
- Machine Learning in Computational Biology (Part 2)
- Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
- Markov Chain Monte Carlo with People
- McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
- Measuring Neural Synchrony by Message Passing
- Mechanisms of Visual Attention
- Message Passing for Max-weight Independent Set
- Mining Internet-Scale Software Repositories
- Modeling homophily and stochastic equivalence in symmetric relational data
- Modeling image patches with a directed hierarchy of Markov random fields
- Modeling Natural Sounds with Modulation Cascade Processes
- Modelling motion primitives and their timing in biologically executed movements
- Multiple Instance Active Learning
- Multiple-Instance Pruning For Learning Efficient Cascade Detectors
- Multi-Stage Monte Carlo Approximation for Fast Generalized Data Summations
- Multi-task Gaussian Process Prediction
- Multi-Task Learning via Conic Programming
- Music, Brain and Cognition. Part 1: Learning the Structure of Music and Its Effects On the Brain
- Music, Brain and Cognition. Part 2: Models of Sound and Cognition
- Nearest-Neighbor-Based Active Learning for Rare Category Detection
- Near-Maximum Entropy Models for Binary Neural Representations of Natural Images
- Neural characterization in partially observed populations of spiking neurons
- New Outer Bounds on the Marginal Polytope
- Non-parametric Modeling of Partially Ranked Data
- Object Recognition by Scene Alignment
- One-Pass Boosting
- On higher-order perceptron algorithms
- Online Linear Regression and Its Application to Model-Based Reinforcement Learning
- On Ranking in Survival Analysis: Bounds on the Concordance Index
- On Sparsity and Overcompleteness in Image Models
- Optimal models of sound localization by barn owls
- Optimal ROC Curve for a Combination of Classifiers
- Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
- Parallelizing Support Vector Machines on Distributed Computers
- People Tracking with the Laplacian Eigenmaps Latent Variable Model
- Population coding of object images based on visual features and its relevance to view invariant representation
- Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
- Predicting human gaze using low-level saliency combined with face detection
- Predicting Human Gaze Using Low-level Saliency Combined with Face Detection
- Predictive Matrix-Variate t Models
- Principles of Learning Problem Design
- Privacy-Preserving Belief Propagation and Sampling
- Probabilistic Matrix Factorization
- Progressive mixture rules are deviation suboptimal
- Projection Methods: Algorithmic Structures, Bregman Projections, and Acceleration Techniques
- Random Features for Large-Scale Kernel Machines
- Random Projections for Manifold Learning
- Random Sampling of States in Dynamic Programming
- Rapid Inference on a novel AND/OR graph: Detection, Segmentation and Parsing of Articulated Deformable Objects in Cluttered Backgrounds
- Receding Horizon Differential Dynamic Programming
- Receptive Fields without Spike-Triggering
- Regret Minimization in Games with Incomplete Information
- Regularized Boost for Semi-Supervised Learning
- Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach
- Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
- Representations and Inference on Probability Distributions
- Resampling Methods for Protein Structure Prediction with Rosetta
- Retrieved context and the discovery of semantic structure
- Robotic Eye Model with Learning of Pulse-Step Saccades
- Robotics Challenges for Machine Learning
- Robust Biped Locomotion Using Simple Low-dimensional Control Policies
- Robust Regression with Twinned Gaussian Processes
- Scan Strategies for Meteorological Radars
- Scene Segmentation with CRFs Learned from Partially Labeled Images
- Second Order Bilinear Discriminant Analysis for single trial EEG analysis
- Selecting Observations against Adversarial Objectives
- Semi-Supervised Multitask Learning
- Sensory Coding and Hierarchical Representations
- Sequential Hypothesis Testing under Stochastic Deadlines
- Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons
- Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains
- SpAM: Sparse Additive Models
- Sparse deep belief net model for visual area V2
- Sparse Feature Learning for Deep Belief Networks
- Sparse Overcomplete Latent Variable Decomposition of Counts Data
- Spatial Latent Dirichlet Allocation
- Stability Bounds for Non-i.i.d. Processes
- Stable Dual Dynamic Programming
- Statistical Analysis of Semi-Supervised Regression
- Statistical Models for Social Networks with Application to HIV Epidemiology
- Statistical Network Models
- Structured Learning with Approximate Inference
- Structured Prediction
- Subspace-Based Face Recognition in Analog VLSI
- Supervised Topic Models
- Support Vector Machine Classification with Indefinite Kernels
- Tekkotsu Cognitive Robotics
- Temporal Difference with Eligibility Traces Derived from First Principles
- Testing for Homogeneity with Kernel Fisher Discriminant Analysis
- The discriminant center-surround hypothesis for bottom-up saliency
- The Distribution Family of Similarity Distances
- The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information
- The Generalized FITC Approximation
- The Grammar of Vision: Probabilistic Grammar-Based Models for Visual Scene Understanding and Object Categorization
- The Infinite Gamma-Poisson Feature Model
- The Infinite Markov Model
- The Noisy-Logical Distribution and its Application to Causal Inference
- Theoretical Analysis of Heuristic Search Methods for Online POMDPs
- Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity
- Theory and Applications of Boosting
- The Price of Bandit Information for Online Optimization
- The rat as particle filter
- The Tradeoffs of Large Scale Learning
- The Urban Challenge – Perspectives of Autonomous Driving
- The Value of Labeled and Unlabeled Examples when the Model is Imperfect
- Topmoumoute Online Natural Gradient Algorithm
- Topology Learning: New Challenges At the Crossing of Machine Learning,
- Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations
- TrueSkill Through Time: Revisiting the History of Chess
- Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks
- Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
- Variational Inference for Diffusion Processes
- Variational inference for Markov jump processes
- Visualization of DepthMotion Perception by Model Cortical Neurons
- Visual Recognition in Primates and Machines
- What makes some POMDP problems easy to approximate?