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author
paper
2008
Preconditioned Temporal Difference Learning (2008)
The GroupLASSO for Generalized Linear Models: uniqueness of solutions and efficient algorithms (2008)
Autonomous geometric precision error estimation in low-level computer vision tasks (2008)
A Worst-Case Comparison Between Temporal Difference and Residual Gradient with Linear Function Approximation (2008)
Dirichlet Component Analysis: Feature Extraction for Compositional Data (2008)
Adaptive p-Posterior Mixture-Model Kernels for Multiple Instance Learning (2008)
Pairwise Constraint Propagation by Semidefinite Programming for Semi-Supervised Classification (2008)
Cost-Sensitive Multi-class Classification From Probability Estimates (2008)
Fast Gaussian Process Methods for Point Process Intensity Estimation (2008)
Localized Multiple Kernel Learning (2008)
Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity (2008)
Uncorrelated Multilinear Principal Component Analysis through Successive Variance Maximization (2008)
A Dual Coordinate Descent Method for Large-scale Linear SVM (2008)
Listwise Approach to Learning to Rank - Theory and Algorithm (2008)
Efficient MultiClass Maximum Margin Clustering (2008)
Spectral clustering with inconsistent advice (2008)
Nearest Hyperdisk Methods for High-Dimensional Classification (2008)
Query-Level Stability and Generalization in Learning to Rank (2008)
Local Likelihood Modeling of Temporal Text Streams (2008)
Inverting the Viterbi Algorithm: An Abstract Framework for Structure Design (2008)
Estimating Local Optimums in EM Algorithm over Gaussian Mixture Model (2008)
Efficiently Learning Linear-Linear Exponential Family Predictive Representations of State (2008)
Learning to Classify with Missing and Corrupted Features (2008)
Multi-Task Compressive Sensing with Dirichlet Process Priors (2008)
Fast Solvers and Efficient Implementations for Distance Metric Learning (2008)
Nu-Support Vector Machine as Conditional Value-at-Risk Minimization (2008)
Manifold Alignment using Procrustes Analysis (2008)
A Decoupled Approach to Exemplar-based Unsupervised Learning. (2008)
Laplace Maximum Margin Markov Networks (2008)
Gaussian Process Product Models for Nonparametric Nonstationarity (2008)
Prediction with expert advice for the Brier game (2008)
Stability of Transductive Regression Algorithms (2008)
Learning All Optimal Policies with Multiple Criteria (2008)
Random classification noise defeats all convex potential boosters (2008)
Non-Parametric Policy Gradients: A Unified Treatment of Propositional and Relational Domains (2008)
On Partial Optimality in Multi-label MRFs (2008)
Learning Diverse Rankings with Multi-Armed Bandits (2008)
SVM Optimization: Inverse Dependence on Training Set Size (2008)
A Least Squares Formulation for Canonical Correlation Analysis (2008)
Learning from Incomplete Data with Infinite Imputations (2008)
Nonextensive Entropic Kernels (2008)
A Distance Model for Rhythms (2008)
Training Structural SVMs when Exact Inference is Intractable (2008)
Active Reinforcement Learning (2008)
Graph Transduction via Alternating Minimization (2008)
Learning to Sportscast: A Test of Grounded Language Acquisition (2008)
An HDP-HMM for Systems with State Persistence (2008)
Fully Distributed EM for Very Large Datasets (2008)
Grassmann Discriminant Analysis: a Unifying View on Subspace-Based Learning (2008)
On-line Discovery of Temporal-Difference Networks (2008)
A Reproducing Kernel Hilbert Space Framework for Pairwise Time Series Distances (2008)
Confidence-Weighted Linear Classification (2008)
On the Chance Accuracies of Large Collections of Classifiers (2008)
Hierarchical sampling for active learning (2008)
Efficiently Solving Convex Relaxations for MAP Estimation (2008)
Boosting with Incomplete Information (2008)
Privacy-Preserving Reinforcement Learning (2008)
Estimating Labels from Label Proportions (2008)
Deep Learning via Semi-Supervised Embedding (2008)
Online Kernel Selection for Bayesian Reinforcement Learning (2008)
Unsupervised Rank Aggregation with Distance-Based Models (2008)
The Projectron: a Bounded Kernel-Based Perceptron (2008)
Efficient Projections onto the L1-Ball for Learning in High Dimensions (2008)
Maximum likelihood rule ensembles (2008)
Rank Minimization via Online Learning (2008)
Topologically-Constrained Latent Variable Models (2008)
Tailoring Density Estimation via Reproducing Kernel Moment Matching (2008)
Graph kernels between point clouds (2008)
Large Scale Manifold Transduction (2008)
On Multi-View Active Learning and the Combination with Semi-Supervised Learning (2008)
Bolasso: Model Consistent Lasso Estimation through the Bootstrap (2008)
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning (2008)
Learning Dissimilarities by Ranking: From SDP to QP (2008)
The skew spectrum of graphs (2008)
Modified MMI/MPE: A Direct Evaluation of the Margin in Speech Recognition (2008)
Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression (2008)
Fast nearest neighbor retrieval for bregman divergences (2008)
Accurate max-margin training for structured output spaces (2008)
Optimized Cutting Plane Algorithm for Support Vector Machines (2008)
Learning to Learn Implicit Queries from Gaze Patterns (2008)
Modeling Interleaved Hidden Processes (2008)
Discriminative Parameter Learning for Bayesian Networks (2008)
Memory Bounded Inference in Topic Models (2008)
A Semiparametric Statistical Approach to Model-Free Policy Evaluation (2008)
Self-taught Clustering (2008)
Active Kernel Learning (2008)
Sequence Kernels for Predicting Protein Essentiality (2008)
Optimizing Estimated Loss Reduction for Active Sampling in Rank Learning (2008)
Robust Matching and Recognition using Context-Dependent Kernels (2008)
Learning for Control from Multiple Demonstrations (2008)
Bayes Optimal Classification for Decision Trees (2008)
Automatic Discovery and Transfer of MAXQ Hierarchies (2008)
Compressed Sensing and Bayesian Experimental Design (2008)
Statistical Models for Partial Membership (2008)
A Quasi-Newton Approach to Nonsmooth Convex Optimization (2008)
Predicting Diverse Subsets Using Structural SVMs (2008)
Improved Nystrom Low-Rank Approximation and Error Analysis (2008)
Transfer of Samples in Batch Reinforcement Learning (2008)
Expectation-Maximization for Sparse and Non-Negative PCA (2008)
Reinforcement Learning with Limited Reinforcement: Using Bayes Risk for Active Learning in POMDPs (2008)
Space-indexed Dynamic Programming: Learning to Follow Trajectories (2008)
Democratic Approximation of Lexicographic Preference Models (2008)
The many faces of optimism: a unifying approach (2008)
Fast Support Vector Machine Training and Classification on Graphics Processors (2008)
Stopping Conditions for Exact Computation of Leave-One-Out Error in Support Vector Machines (2008)
Data Spectroscopy: Learning Mixture Models using Eigenspaces of Convolution Operators (2008)
Fast Estimation of First-Order Clause Coverage through Randomization and Maximum Likelihood (2008)
Efficient Bandit Algorithms for Online Multiclass Prediction (2008)
Polyhedral Classifier for Target Detection A Case Study: Colorectal Cancer (2008)
Exploration Scavenging (2008)
Multi-Task Learning for HIV Therapy Screening (2008)
Empirical Bernstein Stopping (2008)
The Asymptotics of Semi-Supervised Learning in Discriminative Probabilistic Models (2008)
Discriminative Structure and Parameter Learning for Markov Logic Networks (2008)
Training SVM with Indefinite Kernels (2008)
Multi-Classification by Categorical Features via Clustering (2008)
The Dynamic Hierarchical Dirichlet Process (2008)
No-Regret Learning in Convex Games (2008)
Hierarchical Model-Based Reinforcement Learning: R-max + MAXQ (2008)
ICA and ISA Using Schweizer-Wolff Measure of Dependence (2008)
Multiple Instance Ranking (2008)
Hierarchical Kernel Stick-Breaking Process for Multi-Task Image Analysis (2008)
mStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations (2008)
Sample-Based Learning and Search with Permanent and Transient Memories (2008)
Fast Incremental Proximity Search in Large Graphs (2008)
An Object-Oriented Representation for Efficient Reinforcement Learning (2008)
On the Quantitative Analysis of Deep Belief Networks (2008)
Sparse Bayesian nonparametric regression (2008)
Reinforcement Learning in the Presence of Rare Events (2008)
An Analysis of Linear Models, Linear Value-Function Approximation, and Feature Selection for Reinforcement Learning (2008)
Metric Embedding for Kernel Classification Rules (2008)
Bayesian multiple instance learning: automatic feature selection and inductive transfer (2008)
An Analysis of Generative, Discriminative, and Pseudolikelihood Estimators (2008)
Extracting and Composing Robust Features with Denoising Autoencoders (2008)
Sparse Multiscale Gaussian Process Regression (2008)
Bayesian Probabilistic Matrix Factorization using Markov Chain Monte Carlo (2008)
Classification using Discriminative Restricted Boltzmann Machines (2008)
Efficient Deep Learning for Text Classification and Retrieval (2008)
Pointwise exact bootstrap distributions of cost curves (2008)
Knows What It Knows: A Framework For Self-Aware Learning (2008)
A Rate-Distortion One-Class Model and its Applications to Clustering (2008)
Detecting Statistical Interactions with Additive Groves of Trees (2008)
An Empirical Evaluation of Supervised Learning in High Dimensions (2008)
Training Restricted Boltzmann Machines using Approximations to the Likelihood Gradient (2008)
An RKHS for Multi-View Learning and Manifold Co-Regularization (2008)
A generalization of Haussler's convolution kernel - mapping kernel (2008)
Apprenticeship Learning Using Linear Programming (2008)
An analysis of reinforcement learning with function approximation (2008)
Strategy Evaluation in Extensive Games with Importance Sampling (2008)
Composite Kernel Learning (2008)
Nonnegative Matrix Factorization via Rank-One Downdate (2008)
Closed-form Supervised Dimensionality Reduction with Generalized Linear Models (2008)
Structure Compilation: Trading Structure for Features (2008)
ManifoldBoost: Stagewise Function Approximation for Fully-, Semi- and Un-supervised Learning (2008)
Beam Sampling for the Infinite Hidden Markov Model (2008)
Solving graph-structured linear programs: convergence and optimality guarantees (2008)
On the Hardness of Finding Symmetries in Markov Decision Processes (2008)
Actively Learning Level-Sets of Composite Functions (2008)
2009
ICML 2008 - Accepted Papers
ICML 2009 - Accepted Papers
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paper/2008/264.txt · Last modified: 2009/05/24 18:48 (external edit)
