NeurIPS 2014

411 papers

Deep Fragment Embeddings for Bidirectional Image Sentence Mapping

Andrej Karpathy, Armand Joulin, Li F Fei-Fei

Learning Chordal Markov Networks by Dynamic Programming

Kustaa Kangas, Mikko Koivisto, Teppo Niinimäki

Discriminative Unsupervised Feature Learning with Convolutional Neural Networks

Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, Thomas Brox

Message Passing Inference for Large Scale Graphical Models with High Order Potentials

Jian Zhang, Alex Schwing, Raquel Urtasun

On the Number of Linear Regions of Deep Neural Networks

Guido F. Montufar, Razvan Pascanu, Kyunghyun Cho, Yoshua Bengio

Probabilistic ODE Solvers with Runge-Kutta Means

Michael Schober, David K. Duvenaud, Philipp Hennig

Discriminative Metric Learning by Neighborhood Gerrymandering

Shubhendu Trivedi, David Mcallester, Greg Shakhnarovich

Global Sensitivity Analysis for MAP Inference in Graphical Models

Jasper De Bock, Cassio P de Campos, Alessandro Antonucci

Best-Arm Identification in Linear Bandits

Marta Soare, Alessandro Lazaric, Rémi Munos

Generalized Dantzig Selector: Application to the k-support norm

Soumyadeep Chatterjee, Sheng Chen, Arindam Banerjee

Shape and Illumination from Shading using the Generic Viewpoint Assumption

Daniel Zoran, Dilip Krishnan, José Bento, Bill Freeman

Factoring Variations in Natural Images with Deep Gaussian Mixture Models

Aaron van den Oord, Benjamin Schrauwen

Optimistic Planning in Markov Decision Processes Using a Generative Model

Balázs Szörényi, Gunnar Kedenburg, Rémi Munos

Testing Unfaithful Gaussian Graphical Models

De Wen Soh, Sekhar C Tatikonda

Generalized Unsupervised Manifold Alignment

Zhen Cui, Hong Chang, Shiguang Shan, Xilin Chen

Fast Kernel Learning for Multidimensional Pattern Extrapolation

Andrew G Wilson, Elad Gilboa, Arye Nehorai, John P. Cunningham

Bounded Regret for Finite-Armed Structured Bandits

Tor Lattimore, Rémi Munos

Generative Adversarial Nets

Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley

Analysis of Learning from Positive and Unlabeled Data

Marthinus C du Plessis, Gang Niu, Masashi Sugiyama

From MAP to Marginals: Variational Inference in Bayesian Submodular Models

Josip Djolonga, Andreas Krause

Efficient Optimization for Average Precision SVM

Pritish Mohapatra, C.V. Jawahar, M. Pawan Kumar

Distributed Parameter Estimation in Probabilistic Graphical Models

Yariv D Mizrahi, Misha Denil, Nando de Freitas

Discovering Structure in High-Dimensional Data Through Correlation Explanation

Greg Ver Steeg, Aram Galstyan

A Multiplicative Model for Learning Distributed Text-Based Attribute Representations

Ryan Kiros, Richard Zemel, Ruslan Salakhutdinov

Estimation with Norm Regularization

Arindam Banerjee, Sheng Chen, Farideh Fazayeli, Vidyashankar Sivakumar

Active Learning and Best-Response Dynamics

Maria-Florina F Balcan, Christopher Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik

A Latent Source Model for Online Collaborative Filtering

Guy Bresler, George H Chen, Devavrat Shah

On Integrated Clustering and Outlier Detection

Lionel Ott, Linsey Pang, Fabio T Ramos, Sanjay Chawla

PAC-Bayesian AUC classification and scoring

James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang

Zero-shot recognition with unreliable attributes

Dinesh Jayaraman, Kristen Grauman

Divide-and-Conquer Learning by Anchoring a Conical Hull

Tianyi Zhou, Jeff A. Bilmes, Carlos Guestrin

Efficient Minimax Signal Detection on Graphs

Jing Qian, Venkatesh Saligrama

Improved Distributed Principal Component Analysis

Yingyu Liang, Maria-Florina F Balcan, Vandana Kanchanapally, David Woodruff

Mode Estimation for High Dimensional Discrete Tree Graphical Models

Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao

Sparse PCA with Oracle Property

Quanquan Gu, Zhaoran Wang, Han Liu

Reducing the Rank in Relational Factorization Models by Including Observable Patterns

Maximilian Nickel, Xueyan Jiang, Volker Tresp

Greedy Subspace Clustering

Dohyung Park, Constantine Caramanis, Sujay Sanghavi

Unsupervised Transcription of Piano Music

Taylor Berg-Kirkpatrick, Jacob Andreas, Dan Klein

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation

Prateek Jain, Ambuj Tewari, Purushottam Kar

Learning Mixtures of Ranking Models

Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan

Attentional Neural Network: Feature Selection Using Cognitive Feedback

Qian Wang, Jiaxing Zhang, Sen Song, Zheng Zhang

Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning

Francesco Orabona

Partition-wise Linear Models

Hidekazu Oiwa, Ryohei Fujimaki

Discrete Graph Hashing

Wei Liu, Cun Mu, Sanjiv Kumar, Shih-fu Chang

Decomposing Parameter Estimation Problems

Khaled S Refaat, Arthur Choi, Adnan Darwiche

Discovering, Learning and Exploiting Relevance

Cem Tekin, Mihaela van der Schaar

On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification

Yingzhen Yang, Feng Liang, Shuicheng Yan, Zhangyang Wang, Thomas S. Huang

A Dual Algorithm for Olfactory Computation in the Locust Brain

Sina Tootoonian, Máté Lengyel

On the Information Theoretic Limits of Learning Ising Models

Rashish Tandon, Karthikeyan Shanmugam, Pradeep K Ravikumar, Alexandros G Dimakis

Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings

Ian En-Hsu Yen, Cho-jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

Diverse Randomized Agents Vote to Win

Albert Jiang, Leandro Soriano Marcolino, Ariel D Procaccia, Tuomas Sandholm, Nisarg Shah

Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices

Austin R Benson, Jason Lee, Bartek Rajwa, David F Gleich

Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets

Jie Wang, Jieping Ye

Minimax-optimal Inference from Partial Rankings

Bruce Hajek, Sewoong Oh, Jiaming Xu

General Table Completion using a Bayesian Nonparametric Model

Isabel Valera, Zoubin Ghahramani

Approximating Hierarchical MV-sets for Hierarchical Clustering

Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch

Predicting Useful Neighborhoods for Lazy Local Learning

Aron Yu, Kristen Grauman

Reputation-based Worker Filtering in Crowdsourcing

Srikanth Jagabathula, Lakshminarayanan Subramanian, Ashwin Venkataraman

Spectral Clustering of graphs with the Bethe Hessian

Alaa Saade, Florent Krzakala, Lenka Zdeborová

Learning Time-Varying Coverage Functions

Nan Du, Yingyu Liang, Maria-Florina F Balcan, Le Song

Learning Shuffle Ideals Under Restricted Distributions

Dongqu Chen

Online Decision-Making in General Combinatorial Spaces

Arun Rajkumar, Shivani Agarwal

Learning Optimal Commitment to Overcome Insecurity

Avrim Blum, Nika Haghtalab, Ariel D Procaccia

Combinatorial Pure Exploration of Multi-Armed Bandits

Shouyuan Chen, Tian Lin, Irwin King, Michael R Lyu, Wei Chen

(Almost) No Label No Cry

Giorgio Patrini, Richard Nock, Paul Rivera, Tiberio Caetano

Stochastic Network Design in Bidirected Trees

xiaojian wu, Daniel R. Sheldon, Shlomo Zilberstein

Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms

Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun

Recursive Inversion Models for Permutations

Christopher Meek, Marina Meila

Local Linear Convergence of Forward--Backward under Partial Smoothness

Jingwei Liang, Jalal Fadili, Gabriel Peyré

Provable Tensor Factorization with Missing Data

Prateek Jain, Sewoong Oh

Fast Prediction for Large-Scale Kernel Machines

Cho-jui Hsieh, Si Si, Inderjit S Dhillon

Sparse Multi-Task Reinforcement Learning

Daniele Calandriello, Alessandro Lazaric, Marcello Restelli

Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors

Lingqiao Liu, Chunhua Shen, Lei Wang, Anton van den Hengel, Chao Wang

Multi-Scale Spectral Decomposition of Massive Graphs

Si Si, Donghyuk Shin, Inderjit S Dhillon, Beresford N Parlett

Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models

Yarin Gal, Mark van der Wilk, Carl Edward Rasmussen

A statistical model for tensor PCA

Emile Richard, Andrea Montanari

A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation

Eran Treister, Javier S Turek

Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation

Ohad Shamir

Deep Recursive Neural Networks for Compositionality in Language

Ozan Irsoy, Claire Cardie

On the Convergence Rate of Decomposable Submodular Function Minimization

Robert Nishihara, Stefanie Jegelka, Michael I. Jordan, Michael I Jordan

Local Decorrelation For Improved Pedestrian Detection

Woonhyun Nam, Piotr Dollár, Joon Hee Han

Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model

Debarghya Ghoshdastidar, Ambedkar Dukkipati

Two-Stream Convolutional Networks for Action Recognition in Videos

Karen Simonyan, Andrew Zisserman

Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)

Anshumali Shrivastava, Ping Li

Learning with Fredholm Kernels

Qichao Que, Mikhail Belkin, Yusu Wang

Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics

Sergey Levine, Pieter Abbeel

Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights

Daniel Soudry, Itay Hubara, Ron Meir

Positive Curvature and Hamiltonian Monte Carlo

Christof Seiler, Simon Rubinstein-Salzedo, Susan Holmes

Scalable Kernel Methods via Doubly Stochastic Gradients

Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj

A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process

Bahadir Ozdemir, Larry S. Davis

The limits of squared Euclidean distance regularization

Michal Derezinski, Manfred K. Warmuth

A Filtering Approach to Stochastic Variational Inference

Neil Houlsby, David Blei

Sparse Bayesian structure learning with “dependent relevance determination” priors

Anqi Wu, Mijung Park, Oluwasanmi O Koyejo, Jonathan W Pillow

Streaming, Memory Limited Algorithms for Community Detection

Se-Young Yun, marc lelarge, Alexandre Proutiere

Extremal Mechanisms for Local Differential Privacy

Peter Kairouz, Sewoong Oh, Pramod Viswanath

A Synaptical Story of Persistent Activity with Graded Lifetime in a Neural System

Yuanyuan Mi, Luozheng Li, Dahui Wang, Si Wu

Spectral Methods for Supervised Topic Models

Yining Wang, Jun Zhu

Just-In-Time Learning for Fast and Flexible Inference

S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John Winn

Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation

Mingjun Zhong, Nigel Goddard, Charles Sutton

Simple MAP Inference via Low-Rank Relaxations

Roy Frostig, Sida Wang, Percy Liang, Christopher D. Manning