ICML 2015

270 papers

Long Short-Term Memory Over Recursive Structures

Xiaodan Zhu, Parinaz Sobihani, Hongyu Guo

An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process

Amar Shah, David Knowles, Zoubin Ghahramani

Geometric Conditions for Subspace-Sparse Recovery

Chong You, René Vidal

Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees

Mathieu Serrurier, Henri Prade

Non-Stationary Approximate Modified Policy Iteration

Boris Lesner, Bruno Scherrer

K-hyperplane Hinge-Minimax Classifier

Margarita Osadchy, Tamir Hazan, Daniel Keren

Convex Learning of Multiple Tasks and their Structure

Carlo Ciliberto, Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco

Controversy in mechanistic modelling with Gaussian processes

Benn Macdonald, Catherine Higham, Dirk Husmeier

Variational Inference with Normalizing Flows

Danilo Rezende, Shakir Mohamed

On the Rate of Convergence and Error Bounds for LSTD(λ)

Manel Tagorti, Bruno Scherrer

Consistent estimation of dynamic and multi-layer block models

Qiuyi Han, Kevin Xu, Edoardo Airoldi

\ell_1,p-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods

Zirui Zhou, Qi Zhang, Anthony Man-Cho So

Guaranteed Tensor Decomposition: A Moment Approach

Gongguo Tang, Parikshit Shah

Distributed Gaussian Processes

Marc Deisenroth, Jun Wei Ng

Multiview Triplet Embedding: Learning Attributes in Multiple Maps

Ehsan Amid, Antti Ukkonen

DRAW: A Recurrent Neural Network For Image Generation

Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Rezende, Daan Wierstra

Towards a Learning Theory of Cause-Effect Inference

David Lopez-paz, Krikamol Muandet, Bernhard Schölkopf, Iliya Tolstikhin

Risk and Regret of Hierarchical Bayesian Learners

Jonathan Huggins, Josh Tenenbaum

MRA-based Statistical Learning from Incomplete Rankings

Eric Sibony, Stéphan Clémençon, Jérémie Jakubowicz

A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data

Yining Wang, Yu-Xiang Wang, Aarti Singh

CUR Algorithm for Partially Observed Matrices

Miao Xu, Rong Jin, Zhi-Hua Zhou

Strongly Adaptive Online Learning

Amit Daniely, Alon Gonen, Shai Shalev-shwartz

Threshold Influence Model for Allocating Advertising Budgets

Atsushi Miyauchi, Yuni Iwamasa, Takuro Fukunaga, Naonori Kakimura

Convex Formulation for Learning from Positive and Unlabeled Data

Marthinus Du Plessis, Gang Niu, Masashi Sugiyama

The Composition Theorem for Differential Privacy

Peter Kairouz, Sewoong Oh, Pramod Viswanath

Double Nyström Method: An Efficient and Accurate Nyström Scheme for Large-Scale Data Sets

Woosang Lim, Minhwan Kim, Haesun Park, Kyomin Jung

Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood

Kohei Hayashi, Shin-ichi Maeda, Ryohei Fujimaki

Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM

Xiaojun Chang, Yi Yang, Eric Xing, Yaoliang Yu

Metadata Dependent Mondrian Processes

Yi Wang, Bin Li, Yang Wang, Fang Chen

On Greedy Maximization of Entropy

Dravyansh Sharma, Ashish Kapoor, Amit Deshpande

Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games

Julien Pérolat, Bruno Scherrer, Bilal Piot, Olivier Pietquin

Universal Value Function Approximators

Tom Schaul, Daniel Horgan, Karol Gregor, David Silver

Sparse Variational Inference for Generalized GP Models

Rishit Sheth, Yuyang Wang, Roni Khardon

Nested Sequential Monte Carlo Methods

Christian Naesseth, Fredrik Lindsten, Thomas Schön

On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments

Yifan Wu, András György, Csaba Szepesvári

Convergence rate of Bayesian tensor estimator and its minimax optimality

Taiji Suzuki

A Bayesian nonparametric procedure for comparing algorithms

Alessio Benavoli, Giorgio Corani, Francesca Mangili, Marco Zaffalon

Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood

Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin

Dealing with small data: On the generalization of context trees

Ralf Eggeling, Mikko Koivisto, Ivo Grosse

The Power of Randomization: Distributed Submodular Maximization on Massive Datasets

Rafael Barbosa, Alina Ene, Huy Nguyen, Justin Ward

Scalable Model Selection for Large-Scale Factorial Relational Models

Chunchen Liu, Lu Feng, Ryohei Fujimaki, Yusuke Muraoka

Markov Chain Monte Carlo and Variational Inference: Bridging the Gap

Tim Salimans, Diederik Kingma, Max Welling

Multi-Task Learning for Subspace Segmentation

Yu Wang, David Wipf, Qing Ling, Wei Chen, Ian Wassell

Manifold-valued Dirichlet Processes

Hyunwoo Kim, Jia Xu, Baba Vemuri, Vikas Singh

Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure Transfer

Yan-Fu Liu, Cheng-Yu Hsu, Shan-Hung Wu

Unsupervised Domain Adaptation by Backpropagation

Yaroslav Ganin, Victor Lempitsky

Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization

Tyler Johnson, Carlos Guestrin

Faster cover trees

Mike Izbicki, Christian Shelton

Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays

Junpei Komiyama, Junya Honda, Hiroshi Nakagawa

Exponential Integration for Hamiltonian Monte Carlo

Wei-Lun Chao, Justin Solomon, Dominik Michels, Fei Sha

Simple regret for infinitely many armed bandits

Alexandra Carpentier, Michal Valko

Swept Approximate Message Passing for Sparse Estimation

Andre Manoel, Florent Krzakala, Eric Tramel, Lenka Zdeborová

Efficient Learning in Large-Scale Combinatorial Semi-Bandits

Zheng Wen, Branislav Kveton, Azin Ashkan

Safe Subspace Screening for Nuclear Norm Regularized Least Squares Problems

Qiang Zhou, Qi Zhao

Learning Program Embeddings to Propagate Feedback on Student Code

Chris Piech, Jonathan Huang, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami

On Deep Multi-View Representation Learning

Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes

A Probabilistic Model for Dirty Multi-task Feature Selection

Daniel Hernández-lobato, José Miguel Hernández-Lobato, Zoubin Ghahramani

Learning Fast-Mixing Models for Structured Prediction

Jacob Steinhardt, Percy Liang

Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing

Yasin Abbasi-Yadkori, Peter Bartlett, Xi Chen, Alan Malek

Reified Context Models

Jacob Steinhardt, Percy Liang

Following the Perturbed Leader for Online Structured Learning

Alon Cohen, Tamir Hazan

Finding Galaxies in the Shadows of Quasars with Gaussian Processes

Roman Garnett, Shirley Ho, Jeff Schneider

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)

Maurizio Filippone, Raphael Engler

The Ladder: A Reliable Leaderboard for Machine Learning Competitions

Avrim Blum, Moritz Hardt

Safe Exploration for Optimization with Gaussian Processes

Yanan Sui, Alkis Gotovos, Joel Burdick, Andreas Krause

Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM

Ching-pei Lee, Dan Roth

Inferring Graphs from Cascades: A Sparse Recovery Framework

Jean Pouget-Abadie, Thibaut Horel

Bayesian and Empirical Bayesian Forests

Taddy Matthew, Chun-Sheng Chen, Jun Yu, Mitch Wyle

From Word Embeddings To Document Distances

Matt Kusner, Yu Sun, Nicholas Kolkin, Kilian Weinberger

Rademacher Observations, Private Data, and Boosting

Richard Nock, Giorgio Patrini, Arik Friedman

Support Matrix Machines

Luo Luo, Yubo Xie, Zhihua Zhang, Wu-jun Li

A Nearly-Linear Time Framework for Graph-Structured Sparsity

Chinmay Hegde, Piotr Indyk, Ludwig Schmidt

Differentially Private Bayesian Optimization

Matt Kusner, Jacob Gardner, Roman Garnett, Kilian Weinberger

Large-scale log-determinant computation through stochastic Chebyshev expansions

Insu Han, Dmitry Malioutov, Jinwoo Shin

Adaptive Belief Propagation

Georgios Papachristoudis, John Fisher

An Online Learning Algorithm for Bilinear Models

Yuanbin Wu, Shiliang Sun

MADE: Masked Autoencoder for Distribution Estimation

Mathieu Germain, Karol Gregor, Iain Murray, Hugo Larochelle

HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades

Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, Yan Liu

DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics

Yining Wang, Jun Zhu

Message Passing for Collective Graphical Models

Tao Sun, Dan Sheldon, Akshat Kumar

Unsupervised Learning of Video Representations using LSTMs

Nitish Srivastava, Elman Mansimov, Ruslan Salakhudinov

A Linear Dynamical System Model for Text

David Belanger, Sham Kakade

The Hedge Algorithm on a Continuum

Walid Krichene, Maximilian Balandat, Claire Tomlin, Alexandre Bayen

Counterfactual Risk Minimization: Learning from Logged Bandit Feedback

Adith Swaminathan, Thorsten Joachims

Fictitious Self-Play in Extensive-Form Games

Johannes Heinrich, Marc Lanctot, David Silver

Alpha-Beta Divergences Discover Micro and Macro Structures in Data

Karthik Narayan, Ali Punjani, Pieter Abbeel

Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions

Alina Ene, Huy Nguyen

Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models

James Foulds, Shachi Kumar, Lise Getoor

Cascading Bandits: Learning to Rank in the Cascade Model

Branislav Kveton, Csaba Szepesvári, Zheng Wen, Azin Ashkan

Multi-view Sparse Co-clustering via Proximal Alternating Linearized Minimization

Jiangwen Sun, Jin Lu, Tingyang Xu, Jinbo Bi

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

Stephan Gouws, Yoshua Bengio, Greg Corrado

Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing

Rongda Zhu, Quanquan Gu

Asymmetric Transfer Learning with Deep Gaussian Processes

Melih Kandemir

Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification

Zhiwu Huang, Ruiping Wang, Shiguang Shan, Xianqiu Li, Xilin Chen

Off-policy Model-based Learning under Unknown Factored Dynamics

Assaf Hallak, Francois Schnitzler, Timothy Mann, Shie Mannor

Low Rank Approximation using Error Correcting Coding Matrices

Shashanka Ubaru, Arya Mazumdar, Yousef Saad

JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes

Jonathan Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash Mansinghka

Vector-Space Markov Random Fields via Exponential Families

Wesley Tansey, OSCAR HERNAN MADRID PADILLA, Arun Sai Suggala, Pradeep Ravikumar

Stochastic Dual Coordinate Ascent with Adaptive Probabilities

Dominik Csiba, Zheng Qu, Peter Richtarik

Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top

Arun Rajkumar, Suprovat Ghoshal, Lek-Heng Lim, Shivani Agarwal