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Tutorial
Mon Dec 08 09:30 AM -- 11:30 AM (PST) @ Regency D
Prequential Analysis
Tutorial
Mon Dec 08 09:30 AM -- 11:30 AM (PST) @ Regency E/F
Compressed Sensing
Tutorial
Mon Dec 08 01:00 PM -- 03:00 PM (PST) @ Regency E/F
Agnostic Learning: Algorithms and Theory
Tutorial
Mon Dec 08 01:00 PM -- 03:00 PM (PST) @ Regency D
The Neurobiology of Decision Making
Tutorial
Mon Dec 08 03:30 PM -- 05:30 PM (PST) @ Regency D
The Smoothed Analysis of Algorithms
Tutorial
Mon Dec 08 03:30 PM -- 05:30 PM (PST) @ Regency E/F
Statistical Models of Visual Images
Break
Mon Dec 08 06:30 PM -- 07:30 PM (PST)
Opening Banquet
Oral
Mon Dec 08 07:45 PM -- 08:05 PM (PST)
Measures of Clustering Quality: A Working Set of Axioms for Clustering
Session
Mon Dec 08 07:45 PM -- 08:25 PM (PST)
Oral session 1: Clustering
Oral
Mon Dec 08 08:05 PM -- 08:25 PM (PST)
Influence of graph construction on graph-based clustering measures
Session
Mon Dec 08 08:25 PM -- 08:45 PM (PST)
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Mon Dec 08 08:25 PM -- 08:26 PM (PST)
On the Reliability of Clustering Stability in the Large Sample Regime
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Mon Dec 08 08:26 PM -- 08:27 PM (PST)
Spectral Clustering with Perturbed Data
In
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Mon Dec 08 08:27 PM -- 08:28 PM (PST)
A "Shape Aware'' Model for semi-supervised Learning of Objects and its Context
In
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Mon Dec 08 08:28 PM -- 08:29 PM (PST)
One sketch for all: Theory and Application of Conditional Random Sampling
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Mon Dec 08 08:30 PM -- 08:31 PM (PST)
Fast Computation of Posterior Mode in Multi-Level Hierarchical Models
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Mon Dec 08 08:31 PM -- 08:32 PM (PST)
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
In
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Mon Dec 08 08:32 PM -- 08:33 PM (PST)
Efficient Inference in Phylogenetic InDel Trees
In
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Mon Dec 08 08:33 PM -- 08:34 PM (PST)
Large Margin Taxonomy Embedding for Document Categorization
In
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Mon Dec 08 08:34 PM -- 08:35 PM (PST)
Analyzing the Monotonic Feature Abstraction for Text Classification
In
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Mon Dec 08 08:36 PM -- 08:37 PM (PST)
Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization
In
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Mon Dec 08 08:37 PM -- 08:38 PM (PST)
Unsupervised Learning of Visual Sense Models for Polysemous Words
In
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Mon Dec 08 08:38 PM -- 08:39 PM (PST)
Deep Learning with Kernel Regularization for Visual Recognition
In
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Mon Dec 08 08:39 PM -- 08:40 PM (PST)
Evaluating probabilities under high-dimensional latent variable models
In
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Invited Talk
Tue Dec 09 08:30 AM -- 09:30 AM (PST)
Computations in Human Sensorimotor Control
Session
Tue Dec 09 08:30 AM -- 09:50 AM (PST)
Oral session 2: Sensorimotor Control
Oral
Tue Dec 09 09:30 AM -- 09:50 AM (PST)
Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control
Session
Tue Dec 09 09:50 AM -- 10:00 AM (PST)
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Tue Dec 09 09:50 AM -- 09:51 AM (PST)
Unifying the Sensory and Motor Components of Sensorimotor Adaptation
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Tue Dec 09 09:51 AM -- 09:52 AM (PST)
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance
In
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Tue Dec 09 09:52 AM -- 09:53 AM (PST)
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
In
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Tue Dec 09 09:53 AM -- 09:54 AM (PST)
How memory biases affect information transmission: A rational analysis of serial reproduction
In
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Tue Dec 09 09:55 AM -- 09:56 AM (PST)
A rational model of preference learning and choice prediction by children
In
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Tue Dec 09 09:56 AM -- 09:57 AM (PST)
Optimal Response Initiation: Why Recent Experience Matters
In
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Tue Dec 09 09:57 AM -- 09:58 AM (PST)
Analyzing human feature learning as nonparametric Bayesian inference
In
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Tue Dec 09 09:58 AM -- 09:59 AM (PST)
A Massively Parallel Digital Learning Processor
In
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Tue Dec 09 09:59 AM -- 10:00 AM (PST)
Predicting the Geometry of Metal Binding Sites from Protein Sequence
In
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Break
Tue Dec 09 10:00 AM -- 10:30 AM (PST)
Break
Oral
Tue Dec 09 10:30 AM -- 10:50 AM (PST)
Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning
Session
Tue Dec 09 10:30 AM -- 11:50 AM (PST)
Oral session 3: Learning from Reinforcement: Modeling and Control
Oral
Tue Dec 09 10:50 AM -- 11:10 AM (PST)
Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement
Oral
Tue Dec 09 11:10 AM -- 11:30 AM (PST)
Simple Local Models for Complex Dynamical Systems
Oral
Tue Dec 09 11:30 AM -- 11:50 AM (PST)
Policy Search for Motor Primitives in Robotics
Session
Tue Dec 09 11:50 AM -- 12:00 PM (PST)
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Tue Dec 09 11:50 AM -- 11:51 AM (PST)
Multi-task Gaussian Process Learning of Robot Inverse Dynamics
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Tue Dec 09 11:51 AM -- 11:52 AM (PST)
Multi-resolution Exploration in Continuous Spaces
In
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Tue Dec 09 11:52 AM -- 11:53 AM (PST)
Multi-Agent Filtering with Infinitely Nested Beliefs
In
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Tue Dec 09 11:53 AM -- 11:54 AM (PST)
Fitted Q-iteration by Advantage Weighted Regression
In
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Tue Dec 09 11:54 AM -- 11:55 AM (PST)
Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
In
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Tue Dec 09 11:55 AM -- 11:56 AM (PST)
Optimization on a Budget: A Reinforcement Learning Approach
In
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Tue Dec 09 11:56 AM -- 11:57 AM (PST)
Near-optimal Regret Bounds for Reinforcement Learning
In
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Tue Dec 09 11:57 AM -- 11:58 AM (PST)
Algorithms for Infinitely Many-Armed Bandits
In
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Tue Dec 09 11:58 AM -- 11:59 AM (PST)
Mind the Duality Gap: Logarithmic regret algorithms for online optimization
In
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Tue Dec 09 11:59 AM -- 12:00 PM (PST)
An Online Algorithm for Maximizing Submodular Functions
In
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Break
Tue Dec 09 12:00 PM -- 02:00 PM (PST)
Lunch
Invited Talk
Tue Dec 09 02:00 PM -- 03:00 PM (PST)
Online Stochastic Combinatorial Optimization
Session
Tue Dec 09 02:00 PM -- 03:20 PM (PST)
Oral session 4: Combinatorial Approximation
Oral
Tue Dec 09 03:00 PM -- 03:20 PM (PST)
MAS: a multiplicative approximation scheme for probabilistic inference
Session
Tue Dec 09 03:20 PM -- 03:30 PM (PST)
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Tue Dec 09 03:20 PM -- 03:21 PM (PST)
Clusters and Coarse Partitions in LP Relaxations
In
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Tue Dec 09 03:21 PM -- 03:22 PM (PST)
Improved Moves for Truncated Convex Models
In
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Tue Dec 09 03:22 PM -- 03:23 PM (PST)
Learning Bounded Treewidth Bayesian Networks
In
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Tue Dec 09 03:23 PM -- 03:24 PM (PST)
Bayesian Network Score Approximation using a Metagraph Kernel
In
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Tue Dec 09 03:24 PM -- 03:25 PM (PST)
Near-minimax recursive density estimation on the binary hypercube
In
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Tue Dec 09 03:25 PM -- 03:26 PM (PST)
Bounds on marginal probability distributions
In
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Tue Dec 09 03:26 PM -- 03:27 PM (PST)
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
In
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Tue Dec 09 03:29 PM -- 03:30 PM (PST)
Efficient Sampling for Gaussian Process Inference using Control Variables
In
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Break
Tue Dec 09 03:30 PM -- 04:00 PM (PST)
Break
Oral
Tue Dec 09 04:00 PM -- 04:20 PM (PST)
Online Metric Learning and Fast Similarity Search
Session
Tue Dec 09 04:00 PM -- 05:20 PM (PST)
Oral session 5: Fast Output Processing, Novelty Detection and Unlabeled Data
Oral
Tue Dec 09 04:20 PM -- 04:40 PM (PST)
Fast Prediction on a Tree
Oral
Tue Dec 09 04:40 PM -- 05:00 PM (PST)
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Oral
Tue Dec 09 05:00 PM -- 05:20 PM (PST)
Unlabeled data: Now it helps, now it doesn't
Session
Tue Dec 09 05:20 PM -- 05:30 PM (PST)
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Tue Dec 09 05:20 PM -- 05:21 PM (PST)
A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning
In
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Tue Dec 09 05:21 PM -- 05:22 PM (PST)
On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost
In
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Tue Dec 09 05:23 PM -- 05:24 PM (PST)
On the Generalization Ability of Online Strongly Convex Programming Algorithms
In
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Tue Dec 09 05:24 PM -- 05:25 PM (PST)
Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning
In
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Tue Dec 09 05:25 PM -- 05:26 PM (PST)
Sparse Online Learning via Truncated Gradient
In
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Tue Dec 09 05:26 PM -- 05:27 PM (PST)
On the Efficient Minimization of Classification Calibrated Surrogates
In
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Tue Dec 09 05:27 PM -- 05:28 PM (PST)
Exact Convex Confidence-Weighted Learning
In
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Tue Dec 09 05:28 PM -- 05:29 PM (PST)
Breaking Audio CAPTCHAs with Machine Learning Techniques
In
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Tue Dec 09 05:29 PM -- 05:30 PM (PST)
Nonlinear causal discovery with additive noise models
In
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Tue Dec 09 05:30 PM -- 05:31 PM (PST)
Sequential effects: Superstition or rational behavior?
In
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Break
Tue Dec 09 06:00 PM -- 08:00 PM (PST)
Dinner
Demonstration
Tue Dec 09 07:30 PM -- 12:00 AM (PST)
A Pencil Balancing Robot Using Only Spike-based Visual Input
Demonstration
Tue Dec 09 07:30 PM -- 12:00 AM (PST)
High-Accuracy 3D Sensing for Mobile Manipulators
Demonstration
Tue Dec 09 07:30 PM -- 12:00 AM (PST)
Vision Toolkit Based on Hierarchical Temporal Memory
Demonstration
Tue Dec 09 07:30 PM -- 12:00 AM (PST)
Worio: A Web-Scale Machine Learning System
Demonstration
Tue Dec 09 07:30 PM -- 12:00 AM (PST)
MLPACK: Scalable Machine Learning Software
Invited Talk
Wed Dec 10 08:30 AM -- 09:30 AM (PST)
Connectome: the quest to deconstruct the brain
Session
Wed Dec 10 08:30 AM -- 09:50 AM (PST)
Oral session 6: Neural Coding
Oral
Wed Dec 10 09:30 AM -- 09:50 AM (PST)
Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex
Session
Wed Dec 10 09:50 AM -- 10:00 AM (PST)
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Wed Dec 10 09:50 AM -- 09:51 AM (PST)
Characterizing neural dependencies with Poisson copula models
In
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Wed Dec 10 09:51 AM -- 09:52 AM (PST)
A general framework for investigating how far the decoding process in the brain can be simplified
In
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Wed Dec 10 09:52 AM -- 09:53 AM (PST)
Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG
In
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Wed Dec 10 09:53 AM -- 09:54 AM (PST)
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images
In
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Wed Dec 10 09:54 AM -- 09:55 AM (PST)
Artificial Olfactory Brain for Mixture Identification
In
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Wed Dec 10 09:55 AM -- 09:56 AM (PST)
An Algorithm for Microchip Spike Sorting
In
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Wed Dec 10 09:56 AM -- 09:57 AM (PST)
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction
In
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Wed Dec 10 09:57 AM -- 09:58 AM (PST)
An improved estimator of Variance Explained in the presence of noise
In
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Wed Dec 10 09:58 AM -- 09:59 AM (PST)
Interpreting the neural code with Formal Concept Analysis
In
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Wed Dec 10 09:59 AM -- 10:00 AM (PST)
Dynamic Visual Attention: Searching for coding length increments
In
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Break
Wed Dec 10 10:00 AM -- 10:30 AM (PST)
Break
Oral
Wed Dec 10 10:30 AM -- 10:50 AM (PST)
Modeling the effects of memory on human online sentence processing with particle filters
Session
Wed Dec 10 10:30 AM -- 11:50 AM (PST)
Oral session 7: Complex Dynamical Systems: Modeling and Estimation
Oral
Wed Dec 10 10:50 AM -- 11:10 AM (PST)
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Oral
Wed Dec 10 11:10 AM -- 11:30 AM (PST)
Nonrigid Structure from Motion in Trajectory Space
Oral
Wed Dec 10 11:30 AM -- 11:50 AM (PST)
Model selection and velocity estimation using novel priors for motion patterns
Session
Wed Dec 10 11:50 AM -- 12:00 PM (PST)
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Wed Dec 10 11:50 AM -- 11:51 AM (PST)
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
In
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Wed Dec 10 11:51 AM -- 11:52 AM (PST)
A Hierarchical Image Model for Polynomial-Time 2D Parsing
In
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Wed Dec 10 11:52 AM -- 11:53 AM (PST)
Learning a discriminative hidden part model for human action recognition
In
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Wed Dec 10 11:53 AM -- 11:54 AM (PST)
Learning Transformational Invariants from Time-Varying Natural Images
In
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Wed Dec 10 11:54 AM -- 11:55 AM (PST)
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
In
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Wed Dec 10 11:55 AM -- 11:56 AM (PST)
The Infinite Factorial Hidden Markov Model
In
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Wed Dec 10 11:56 AM -- 11:57 AM (PST)
Mixed Membership Stochastic Blockmodels
In
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Wed Dec 10 11:58 AM -- 11:59 AM (PST)
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
In
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Wed Dec 10 11:59 AM -- 12:00 PM (PST)
Using matrices to model symbolic relationship
In
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Break
Wed Dec 10 12:00 PM -- 02:00 PM (PST)
Lunch
Invited Talk
Wed Dec 10 02:00 PM -- 03:00 PM (PST)
Machine Learning in High Energy Physics
Session
Wed Dec 10 02:00 PM -- 03:20 PM (PST)
Oral session 8: Physics and High Order Statistics
Oral
Wed Dec 10 03:00 PM -- 03:20 PM (PST)
Characteristic Kernels on Groups and Semigroups
Session
Wed Dec 10 03:20 PM -- 03:30 PM (PST)
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Wed Dec 10 03:20 PM -- 03:21 PM (PST)
Kernel Measures of Independence for non-iid Data
In
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Wed Dec 10 03:22 PM -- 03:23 PM (PST)
Scalable Algorithms for String Kernels with Inexact Matching
In
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Wed Dec 10 03:24 PM -- 03:25 PM (PST)
Learning with Consistency between Inductive Functions and Kernels
In
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Wed Dec 10 03:25 PM -- 03:26 PM (PST)
Performance analysis for L_2 kernel classification
In
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Wed Dec 10 03:26 PM -- 03:27 PM (PST)
Clustered Multi-Task Learning: A Convex Formulation
In
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Wed Dec 10 03:27 PM -- 03:28 PM (PST)
Domain Adaptation with Multiple Sources
In
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Wed Dec 10 03:28 PM -- 03:29 PM (PST)
Phase transitions for high-dimensional joint support recovery
In
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Break
Wed Dec 10 03:30 PM -- 04:00 PM (PST)
Break
Oral
Wed Dec 10 04:00 PM -- 04:20 PM (PST)
Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models
Session
Wed Dec 10 04:00 PM -- 05:20 PM (PST)
Oral session 9: Sparse Learning and Ranking
Oral
Wed Dec 10 04:20 PM -- 04:40 PM (PST)
An interior-point stochastic approximation method and an L1-regularized delta rule
Oral
Wed Dec 10 04:40 PM -- 05:00 PM (PST)
Global Ranking Using Continuous Conditional Random Fields
Oral
Wed Dec 10 05:00 PM -- 05:20 PM (PST)
Inferring rankings under constrained sensing
Session
Wed Dec 10 05:20 PM -- 05:30 PM (PST)
Spotlights
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Wed Dec 10 05:20 PM -- 05:21 PM (PST)
Nonparametric regression and classification with joint sparsity constraints
In
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Wed Dec 10 05:22 PM -- 05:23 PM (PST)
High-dimensional union support recovery in multivariate regression
In
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Wed Dec 10 05:23 PM -- 05:24 PM (PST)
Sparse Signal Recovery Using Markov Random Fields
In
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Wed Dec 10 05:26 PM -- 05:27 PM (PST)
Robust Kernel Principal Component Analysis
In
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Wed Dec 10 05:28 PM -- 05:29 PM (PST)
ICA based on a Smooth Estimation of the Differential Entropy
In
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Break
Wed Dec 10 06:00 PM -- 08:00 PM (PST)
Dinner
Demonstration
Wed Dec 10 07:30 PM -- 12:00 AM (PST)
Demonstrations
Demonstration
Wed Dec 10 07:30 PM -- 12:00 AM (PST)
Visualizing NIPS Cooperations using Multiple Maps t-SNE
Demonstration
Wed Dec 10 07:30 PM -- 12:00 AM (PST)
Infer.NET: Software for Graphical Models
Demonstration
Wed Dec 10 07:30 PM -- 12:00 AM (PST)
RL-Glue: From Grid Worlds to Sensor Rich Robots
Demonstration
Wed Dec 10 07:30 PM -- 12:00 AM (PST)
The Chiara: A New Robotic Platform for Education and Research
Demonstration
Wed Dec 10 07:30 PM -- 12:00 AM (PST)
Machine Perception for Human Machine Interaction
Oral
Thu Dec 11 08:30 AM -- 08:50 AM (PST)
The Mondrian Process
Session
Thu Dec 11 08:30 AM -- 10:10 AM (PST)
Oral session 10: Nonparametric Processes, Scene Processing and Image Statistics
Oral
Thu Dec 11 08:50 AM -- 09:10 AM (PST)
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes
Oral
Thu Dec 11 09:10 AM -- 09:30 AM (PST)
Cascaded Classification Models: Combining Models for Holistic Scene Understanding
Oral
Thu Dec 11 09:30 AM -- 09:50 AM (PST)
Multi-Level Active Prediction of Useful Image Annotations for Recognition
Oral
Thu Dec 11 09:50 AM -- 10:10 AM (PST)
Reducing statistical dependencies in natural signals using radial Gaussianization
Break
Thu Dec 11 10:10 AM -- 10:40 AM (PST)
Break
Oral
Thu Dec 11 10:40 AM -- 11:00 AM (PST)
Load and Attentional Bayes
Session
Thu Dec 11 10:40 AM -- 12:00 PM (PST)
Oral session 11: Attention and Mind
Invited Talk
Thu Dec 11 11:00 AM -- 12:00 PM (PST)
Theory of Mind with fMRI
Break
Thu Dec 11 12:00 PM -- 01:00 PM (PST)
Lunch
Mini Symposium
Thu Dec 11 01:30 PM -- 04:30 PM (PST)
Algebraic methods in machine learning
Mini Symposium
Thu Dec 11 01:30 PM -- 04:30 PM (PST)
Principled Theoretical Frameworks for the Perception-Action Cycle
Mini Symposium
Thu Dec 11 01:30 PM -- 04:30 PM (PST)
Mini Symposia
Mini Symposium
Thu Dec 11 01:30 PM -- 04:30 PM (PST)
Machine Learning in Computational Biology
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Sutcliffe B
Structured Input - Structured Output
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Westin: Glacier
Principled Theoretical Frameworks for the Perception-Action Cycle
Workshop
Fri Dec 12 07:30 AM -- 07:00 PM (PST) @ Westin: Nordic
Causality: objectives and assessment
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Westin: Callaghan
Algebraic and combinatorial methods in machine learning
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Mt. Currie S
Machine Learning in Computational Biology
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Black Tusk
Machine learning meets human learning
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Mt. Currie N
Statistical Analysis and Modeling of Response Dependencies in Neural Populations (day 1)
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Westin: Alpine AB
Analyzing Graphs: Theory and Applications
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Cheakamus
Speech and Language: Learning-based Methods and Systems
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Westin: Emerald A
Beyond Search: Computational Intelligence for the Web (day 1)
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Westin: Alpine CD
Machine Learning Open Source Software
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Diamond Head
Optimization for Machine Learning
Workshop
Fri Dec 12 07:30 AM -- 07:00 PM (PST) @ Westin: Alpine E
Cost Sensitive Learning
Workshop
Fri Dec 12 07:30 AM -- 06:30 PM (PST) @ Hilton: Sutcliffe A
New Challanges in Theoretical Machine Learning: Data Dependent Concept Spaces
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Westin: Alpine E
Learning from Multiple Sources
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Westin: Nordic
Kernel Learning: Automatic Selection of Optimal Kernels
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Hilton: Black Tusk
Stochastic Models of Behaviour
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Westin: Emerald A
Beyond Search: Computational Intelligence for the Web (day 2)
Workshop
Sat Dec 13 07:30 AM -- 07:00 PM (PST) @ Westin: Alpine AB
Approximate inference - how far have we come?
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Hilton: Cheakamus
Speech and Language: Unsupervised Latent-Variable Models
Workshop
Sat Dec 13 07:30 AM -- 07:00 PM (PST) @ Hilton: Sutcliffe B
New Directions in Statistical Learning for Meaningful and Reproducible fMRI Analysis
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Hilton: Sutcliffe A
Parallel Implementations of Learning Algorithms: What have you done for me lately?
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Hilton: Mt. Currie N
Statistical Analysis and Modeling of Response Dependencies in Neural Populations (day 2)
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Westin: Callaghan
Model Uncertainty and Risk in Reinforcement Learning
Workshop
Sat Dec 13 07:30 AM -- 06:30 PM (PST) @ Westin: Alpine CD
Probabilistic Programming: Universal Languages, Systems and Applications
Workshop
Sat Dec 13 07:30 AM -- 07:00 PM (PST) @ Hilton: Diamond Head
Cortical Microcircuits and their Computational Functions