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