ICML 2013

283 papers

Estimation of Causal Peer Influence Effects

Panos Toulis, Edward Kao

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning

Jeffrey Ho, Yuchen Xie, Baba Vemuri

Coco-Q: Learning in Stochastic Games with Side Payments

Eric Sodomka, Elizabeth Hilliard, Michael Littman, Amy Greenwald

Adaptive Hamiltonian and Riemann Manifold Monte Carlo

Ziyu Wang, Shakir Mohamed, Nando Freitas

Online Learning under Delayed Feedback

Pooria Joulani, András György, Csaba Szepesvári

Multilinear Multitask Learning

Bernardino Romera-Paredes, Hane Aung, Nadia Bianchi-Berthouze, Massimiliano Pontil

Tree-Independent Dual-Tree Algorithms

Ryan Curtin, William March, Parikshit Ram, David Anderson, Alexander Gray

Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling

Amr Ahmed, Liangjie Hong, Alexander Smola

Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration

Volodymyr Kuleshov

Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models

Umut Simsekli, Ali Taylan Cemgil, Yusuf Kenan Yilmaz

Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion

Jinfeng Yi, Lijun Zhang, Rong Jin, Qi Qian, Anil Jain

Cost-sensitive Multiclass Classification Risk Bounds

Bernardo Avila Pires, Csaba Szepesvári, Mohammad Ghavamzadeh

Safe Screening of Non-Support Vectors in Pathwise SVM Computation

Kohei Ogawa, Yoshiki Suzuki, Ichiro Takeuchi

Manifold Preserving Hierarchical Topic Models for Quantization and Approximation

Minje Kim, Paris Smaragdis

Learning Policies for Contextual Submodular Prediction

Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, Drew Bagnell

Scale Invariant Conditional Dependence Measures

Sashank J Reddi, Barnabás Póczos

Nonparametric Mixture of Gaussian Processes with Constraints

James Ross, Jennifer Dy

Deep learning with COTS HPC systems

Adam Coates, Brody Huval, Tao Wang, David Wu, Bryan Catanzaro

Predictable Dual-View Hashing

Mohammad Rastegari, Jonghyun Choi, Shobeir Fakhraei, Daume Hal, Larry Davis

Maxout Networks

Ian Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio

On the difficulty of training recurrent neural networks

Razvan Pascanu, Tomas Mikolov, Yoshua Bengio

Learning Triggering Kernels for Multi-dimensional Hawkes Processes

Ke Zhou, Hongyuan Zha, Le Song

Multiple-source cross-validation

Krzysztof Geras, Charles Sutton

Expensive Function Optimization with Stochastic Binary Outcomes

Matthew Tesch, Jeff Schneider, Howie Choset

Fast Image Tagging

Minmin Chen, Alice Zheng, Kilian Weinberger

Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting

Matt Wytock, Zico Kolter

Consistency of Online Random Forests

Misha Denil, David Matheson, Nando Freitas

Deep Canonical Correlation Analysis

Galen Andrew, Raman Arora, Jeff Bilmes, Karen Livescu

Almost Optimal Exploration in Multi-Armed Bandits

Zohar Karnin, Tomer Koren, Oren Somekh

The Bigraphical Lasso

Alfredo Kalaitzis, John Lafferty, Neil D. Lawrence, Shuheng Zhou

Selective sampling algorithms for cost-sensitive multiclass prediction

Alekh Agarwal

Bayesian Learning of Recursively Factored Environments

Marc Bellemare, Joel Veness, Michael Bowling

Topic Discovery through Data Dependent and Random Projections

Weicong Ding, Mohammad Hossein Rohban, Prakash Ishwar, Venkatesh Saligrama

The Cross-Entropy Method Optimizes for Quantiles

Sergiu Goschin, Ari Weinstein, Michael Littman

Smooth Operators

Steffen Grünewälder, Gretton Arthur, John Shawe-Taylor

Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events

Lisa Friedland, David Jensen, Michael Lavine

Structure Discovery in Nonparametric Regression through Compositional Kernel Search

David Duvenaud, James Lloyd, Roger Grosse, Joshua Tenenbaum, Ghahramani Zoubin

Intersecting singularities for multi-structured estimation

Emile Richard, Francis Bach, Jean-philippe Vert

A non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines

Kostadin Georgiev, Preslav Nakov

On the importance of initialization and momentum in deep learning

Ilya Sutskever, James Martens, George Dahl, Geoffrey Hinton

Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization

Krzysztof Dembczynski, Arkadiusz Jachnik, Wojciech Kotlowski, Willem Waegeman, Eyke Huellermeier

O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions

Lijun Zhang, Tianbao Yang, Rong Jin, Xiaofei He

Exploiting Ontology Structures and Unlabeled Data for Learning

Nina Balcan, Avrim Blum, Yishay Mansour

The Extended Parameter Filter

Yusuf Bugra Erol, Lei Li, Bharath Ramsundar, Russell Stuart

Top-k Selection based on Adaptive Sampling of Noisy Preferences

Róbert Busa-Fekete, Balázs Szörényi, Weiwei Cheng, Paul Weng, Eyke Huellermeier

Algorithms for Direct 0–1 Loss Optimization in Binary Classification

Tan Nguyen, Scott Sanner

Anytime Representation Learning

Zhixiang Xu, Matt Kusner, Gao Huang, Kilian Weinberger

Gaussian Process Kernels for Pattern Discovery and Extrapolation

Andrew Wilson, Ryan Adams

Regularization of Neural Networks using DropConnect

Li Wan, Matthew Zeiler, Sixin Zhang, Yann Le Cun, Rob Fergus

Distribution to Distribution Regression

Junier Oliva, Barnabás Póczos, Jeff Schneider

Spectral Experts for Estimating Mixtures of Linear Regressions

Arun Tejasvi Chaganty, Percy Liang

The lasso, persistence, and cross-validation

Darren Homrighausen, Daniel McDonald

Mini-Batch Primal and Dual Methods for SVMs

Martin Takac, Avleen Bijral, Peter Richtarik, Nati Srebro

Scaling the Indian Buffet Process via Submodular Maximization

Colorado Reed, Ghahramani Zoubin

Approximate Inference in Collective Graphical Models

Daniel Sheldon, Tao Sun, Akshat Kumar, Tom Dietterich

Breaking the Small Cluster Barrier of Graph Clustering

Nir Ailon, Yudong Chen, Huan Xu

Natural Image Bases to Represent Neuroimaging Data

Ashish Gupta, Murat Ayhan, Anthony Maida

Fast Max-Margin Matrix Factorization with Data Augmentation

Minjie Xu, Jun Zhu, Bo Zhang

Dependent Normalized Random Measures

Changyou Chen, Vinayak Rao, Wray Buntine, Yee Whye Teh

Modeling Temporal Evolution and Multiscale Structure in Networks

Tue Herlau, Morten Mørup, Mikkel Schmidt

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models

Mohammad Emtiyaz Khan, Aleksandr Aravkin, Michael Friedlander, Matthias Seeger

Stability and Hypothesis Transfer Learning

Ilja Kuzborskij, Francesco Orabona

Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner

peng sun, Jie Zhou

Concurrent Reinforcement Learning from Customer Interactions

David Silver, Leonard Newnham, David Barker, Suzanne Weller, Jason McFall

Learning Convex QP Relaxations for Structured Prediction

Jeremy Jancsary, Sebastian Nowozin, Carsten Rother

One-Pass AUC Optimization

Wei Gao, Rong Jin, Shenghuo Zhu, Zhi-Hua Zhou

Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines

Kohei Ogawa, Motoki Imamura, Ichiro Takeuchi, Masashi Sugiyama

Robust Regression on MapReduce

Xiangrui Meng, Michael Mahoney

Quantile Regression for Large-scale Applications

Jiyan Yang, Xiangrui Meng, Michael Mahoney

Learning the Structure of Sum-Product Networks

Robert Gens, Domingos Pedro

Kernelized Bayesian Matrix Factorization

Mehmet Gönen, Suleiman Khan, Samuel Kaski

Fast Semidifferential-based Submodular Function Optimization

Rishabh Iyer, Stefanie Jegelka, Jeff Bilmes

Max-Margin Multiple-Instance Dictionary Learning

Xinggang Wang, Baoyuan Wang, Xiang Bai, Wenyu Liu, Zhuowen Tu

Stable Coactive Learning via Perturbation

Karthik Raman, Thorsten Joachims, Pannaga Shivaswamy, Tobias Schnabel

Collective Stability in Structured Prediction: Generalization from One Example

Ben London, Bert Huang, Ben Taskar, Lise Getoor

Domain Adaptation under Target and Conditional Shift

Kun Zhang, Bernhard Schölkopf, Krikamol Muandet, Zhikun Wang

Feature Multi-Selection among Subjective Features

Sivan Sabato, Adam Kalai

Consistency versus Realizable H-Consistency for Multiclass Classification

Phil Long, Rocco Servedio

Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Anticipation

Hema Koppula, Ashutosh Saxena

Optimization with First-Order Surrogate Functions

Julien Mairal

Robust Sparse Regression under Adversarial Corruption

Yudong Chen, Constantine Caramanis, Shie Mannor

Exact Rule Learning via Boolean Compressed Sensing

Dmitry Malioutov, Kush Varshney

Computation-Risk Tradeoffs for Covariance-Thresholded Regression

Dinah Shender, John Lafferty

Sparse PCA through Low-rank Approximations

Dimitris Papailiopoulos, Alexandros Dimakis, Stavros Korokythakis

A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers

Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant

Infinite Markov-Switching Maximum Entropy Discrimination Machines

Sotirios Chatzis

On autoencoder scoring

Hanna Kamyshanska, Roland Memisevic

LDA Topic Model with Soft Assignment of Descriptors to Words

Daphna Weinshall, Gal Levi, Dmitri Hanukaev

On learning parametric-output HMMs

Aryeh Kontorovich, Boaz Nadler, Roi Weiss

Sharp Generalization Error Bounds for Randomly-projected Classifiers

Robert Durrant, Ata Kaban

ABC Reinforcement Learning

Christos Dimitrakakis, Nikolaos Tziortziotis

Better Rates for Any Adversarial Deterministic MDP

Ofer Dekel, Elad Hazan

Modeling Information Propagation with Survival Theory

Manuel Gomez-Rodriguez, Jure Leskovec, Bernhard Schölkopf

Factorial Multi-Task Learning : A Bayesian Nonparametric Approach

Sunil Gupta, Dinh Phung, Svetha Venkatesh

Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training

Michael Izbicki

Analogy-preserving Semantic Embedding for Visual Object Categorization

Sung Ju Hwang, Kristen Grauman, Fei Sha

Spectral Learning of Hidden Markov Models from Dynamic and Static Data

Tzu-kuo Huang, Jeff Schneider

Online Kernel Learning with a Near Optimal Sparsity Bound

Lijun Zhang, Jinfeng Yi, Rong Jin, Ming Lin, Xiaofei He

Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment

Jason Chuang, Sonal Gupta, Christopher Manning, Jeffrey Heer

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance

Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal, Sanjay Chawla