NeurIPS 2013

360 papers

How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal

Jacob Abernethy, Rafael Frongillo, Andre Wibisono, Peter L. Bartlett, Peter L Bartlett

Action from Still Image Dataset and Inverse Optimal Control to Learn Task Specific Visual Scanpaths

Stefan Mathe, Cristian Sminchisescu

Aggregating Optimistic Planning Trees for Solving Markov Decision Processes

Gunnar Kedenburg, Raphael Fonteneau, Rémi Munos

Learning from Limited Demonstrations

Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau, Doina Precup

Learning to Prune in Metric and Non-Metric Spaces

Leonid Boytsov, Bilegsaikhan Naidan

Two-Target Algorithms for Infinite-Armed Bandits with Bernoulli Rewards

Thomas Bonald, Alexandre Proutiere

Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion

Nguyen Viet Cuong, Wee Sun Lee, Nan Ye, Kian Ming A Chai, Hai Leong Chieu

Blind Calibration in Compressed Sensing using Message Passing Algorithms

Christophe Schulke, Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová

Annealing between distributions by averaging moments

Roger B Grosse, Chris J Maddison, Ruslan Salakhutdinov

Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs

Tejas D Kulkarni, Yura N Perov, Josh Tenenbaum, Vikash K. Mansinghka, Vikash K Mansinghka

Mid-level Visual Element Discovery as Discriminative Mode Seeking

Carl Doersch, Abhinav Gupta, Alexei A Efros

Bayesian entropy estimation for binary spike train data using parametric prior knowledge

Evan W Archer, ll Memming Park, Jonathan W Pillow

Learning Kernels Using Local Rademacher Complexity

Corinna Cortes, Marius Kloft, Mehryar Mohri

A simple example of Dirichlet process mixture inconsistency for the number of components

Jeffrey W Miller, Matthew T Harrison

Deep Neural Networks for Object Detection

Christian Szegedy, Alexander Toshev, Dumitru Erhan

Mixed Optimization for Smooth Functions

Mehrdad Mahdavi, Lijun Zhang, Rong Jin

Adaptive Step-Size for Policy Gradient Methods

Matteo Pirotta, Marcello Restelli, Luca Bascetta

Lexical and Hierarchical Topic Regression

Viet-An Nguyen, Jordan L Ying, Philip Resnik

Approximate inference in latent Gaussian-Markov models from continuous time observations

Botond Cseke, Manfred Opper, Guido Sanguinetti

Adaptive Submodular Maximization in Bandit Setting

Victor Gabillon, Branislav Kveton, Zheng Wen, Brian Eriksson, S. Muthukrishnan

Noise-Enhanced Associative Memories

Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney

First-order Decomposition Trees

Nima Taghipour, Jesse Davis, Hendrik Blockeel

Using multiple samples to learn mixture models

Jason Lee, Ran Gilad-Bachrach, Rich Caruana

Multi-Task Bayesian Optimization

Kevin Swersky, Jasper Snoek, Ryan P. Adams

Firing rate predictions in optimal balanced networks

David G Barrett, Sophie Deneve, Christian K. Machens

Beyond Pairwise: Provably Fast Algorithms for Approximate k-Way Similarity Search

Anshumali Shrivastava, Ping Li

Optimization, Learning, and Games with Predictable Sequences

Sasha Rakhlin, Karthik Sridharan

Provable Subspace Clustering: When LRR meets SSC

Yu-Xiang Wang, Huan Xu, Chenlei Leng

Robust Data-Driven Dynamic Programming

Grani Adiwena Hanasusanto, Daniel Huhn

Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima

Po-ling Loh, Martin J. Wainwright

Spike train entropy-rate estimation using hierarchical Dirichlet process priors

Karin C Knudson, Jonathan W Pillow

Learning Adaptive Value of Information for Structured Prediction

David J Weiss, Ben Taskar

k-Prototype Learning for 3D Rigid Structures

Hu Ding, Ronald Berezney, Jinhui Xu

Probabilistic Principal Geodesic Analysis

Miaomiao Zhang, Tom Fletcher

Actor-Critic Algorithms for Risk-Sensitive MDPs

Prashanth L.A., Mohammad Ghavamzadeh

Density estimation from unweighted k-nearest neighbor graphs: a roadmap

Ulrike Von Luxburg, Morteza Alamgir

Mapping paradigm ontologies to and from the brain

Yannick Schwartz, Bertrand Thirion, Gael Varoquaux

One-shot learning and big data with n=2

Lee H Dicker, Dean P. Foster

Unsupervised Spectral Learning of Finite State Transducers

Raphael Bailly, Xavier Carreras, Ariadna Quattoni

A Stability-based Validation Procedure for Differentially Private Machine Learning

Kamalika Chaudhuri, Staal A Vinterbo

Binary to Bushy: Bayesian Hierarchical Clustering with the Beta Coalescent

Yuening Hu, Jordan L Ying, Hal Daume III, Z. Irene Ying

Message Passing Inference with Chemical Reaction Networks

Nils E Napp, Ryan P. Adams

Speedup Matrix Completion with Side Information: Application to Multi-Label Learning

Miao Xu, Rong Jin, Zhi-Hua Zhou

Probabilistic Movement Primitives

Alexandros Paraschos, Christian Daniel, Gerhard Neumann, Jan R. Peters, Jan R Peters

Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising

Forest Agostinelli, Michael R Anderson, Honglak Lee

Linear decision rule as aspiration for simple decision heuristics

Ozgur Simsek

Understanding variable importances in forests of randomized trees

Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts

Regret based Robust Solutions for Uncertain Markov Decision Processes

Asrar Ahmed, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet

Policy Shaping: Integrating Human Feedback with Reinforcement Learning

Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L Isbell, Andrea L Thomaz

Minimax Optimal Algorithms for Unconstrained Linear Optimization

Brendan Mcmahan, Jacob Abernethy

Projected Natural Actor-Critic

Philip S. Thomas, William C Dabney, Stephen Giguere, Sridhar Mahadevan

Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent

Tianbao Yang

Learning a Deep Compact Image Representation for Visual Tracking

Naiyan Wang, Dit-Yan Yeung

Reconciling "priors" & "priors" without prejudice?

Remi Gribonval, Pierre Machart

Generalized Method-of-Moments for Rank Aggregation

Hossein Azari Soufiani, William Chen, David C. Parkes, Lirong Xia

Learning word embeddings efficiently with noise-contrastive estimation

Andriy Mnih, Koray Kavukcuoglu

Structured Learning via Logistic Regression

Justin Domke

Reciprocally Coupled Local Estimators Implement Bayesian Information Integration Distributively

Si Wu, Wenhao Zhang, Wen-Hao Zhang

A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data

Jasper Snoek, Richard Zemel, Ryan P. Adams

Robust Transfer Principal Component Analysis with Rank Constraints

Yuhong Guo

Learning Stochastic Feedforward Neural Networks

Charlie Tang, Ruslan Salakhutdinov

Information-theoretic lower bounds for distributed statistical estimation with communication constraints

Yuchen Zhang, John Duchi, Martin J. Wainwright, Michael I. Jordan, Michael I Jordan

When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements

Divyanshu Vats, Richard Baraniuk

Locally Adaptive Bayesian Multivariate Time Series

Daniele Durante, Bruno Scarpa, David B. Dunson, David B Dunson

Memoized Online Variational Inference for Dirichlet Process Mixture Models

Michael C Hughes, Erik Sudderth

Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies

Yangqing Jia, Joshua T. Abbott, Tom Griffiths, Trevor Darrell, Joseph L. Austerweil

Rapid Distance-Based Outlier Detection via Sampling

Mahito Sugiyama, Karsten Borgwardt

Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems

Hesham Mostafa, Lorenz. K Mueller, Giacomo Indiveri

Bayesian inference as iterated random functions with applications to sequential inference in graphical models

Arash Amini, Xuanlong Nguyen

Cluster Trees on Manifolds

Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry Wasserman

Scoring Workers in Crowdsourcing: How Many Control Questions are Enough?

Qiang Liu, Alex Ihler, Mark Steyvers

On Flat versus Hierarchical Classification in Large-Scale Taxonomies

Rohit Babbar, Ioannis Partalas, Eric Gaussier, Massih R. Amini

Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition

Tzu-kuo Huang, Jeff Schneider

Summary Statistics for Partitionings and Feature Allocations

Isik B Fidaner, Taylan Cemgil

Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPs

Liam C MacDermed, Charles L Isbell

The Fast Convergence of Incremental PCA

Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund

(Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings

Abhradeep Guha Thakurta, Adam Smith

Generalized Random Utility Models with Multiple Types

Hossein Azari Soufiani, Hansheng Diao, Zhenyu Lai, David C. Parkes

Relevance Topic Model for Unstructured Social Group Activity Recognition

Fang Zhao, Yongzhen Huang, Liang Wang, Tieniu Tan

Modeling Clutter Perception using Parametric Proto-object Partitioning

Chen-Ping Yu, Wen-Yu Hua, Dimitris Samaras, Greg Zelinsky

Neural representation of action sequences: how far can a simple snippet-matching model take us?

Cheston Tan, Jedediah M Singer, Thomas Serre, David Sheinberg, Tomaso Poggio

Speeding up Permutation Testing in Neuroimaging

Chris Hinrichs, Vamsi K Ithapu, Qinyuan Sun, Sterling C Johnson, Vikas Singh

DESPOT: Online POMDP Planning with Regularization

Adhiraj Somani, Nan Ye, David Hsu, Wee Sun Lee

A New Convex Relaxation for Tensor Completion

Bernardino Romera-Paredes, Massimiliano Pontil

Curvature and Optimal Algorithms for Learning and Minimizing Submodular Functions

Rishabh K Iyer, Stefanie Jegelka, Jeff A. Bilmes

Learning Chordal Markov Networks by Constraint Satisfaction

Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik Nyman, Johan Pensar

Learning Trajectory Preferences for Manipulators via Iterative Improvement

Ashesh Jain, Brian Wojcik, Thorsten Joachims, Ashutosh Saxena

Non-Linear Domain Adaptation with Boosting

Carlos J Becker, Christos M Christoudias, Pascal Fua

On the Sample Complexity of Subspace Learning

Alessandro Rudi, Guillermo D Canas, Lorenzo Rosasco

Context-sensitive active sensing in humans

Sheeraz Ahmad, He Huang, Angela J. Yu

Parallel Sampling of DP Mixture Models using Sub-Cluster Splits

Jason Chang, John W. Fisher III

Efficient Exploration and Value Function Generalization in Deterministic Systems

Zheng Wen, Benjamin Van Roy

On Algorithms for Sparse Multi-factor NMF

Siwei Lyu, Xin Wang

More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server

Qirong Ho, James Cipar, Henggang Cui, Seunghak Lee, Jin Kyu Kim

Stochastic blockmodel approximation of a graphon: Theory and consistent estimation

Edoardo M. Airoldi, Thiago B Costa, Stanley H Chan

Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models

Adel Javanmard, Andrea Montanari

Latent Structured Active Learning

Wenjie Luo, Alex Schwing, Raquel Urtasun

Analyzing Hogwild Parallel Gaussian Gibbs Sampling

Matthew J Johnson, James Saunderson, Alan Willsky

What do row and column marginals reveal about your dataset?

Behzad Golshan, John Byers, Evimaria Terzi

Deep content-based music recommendation

Aaron van den Oord, Sander Dieleman, Benjamin Schrauwen