NeurIPS 2012

370 papers

Gradient Weights help Nonparametric Regressors

Samory Kpotufe, Abdeslam Boularias

Optimal Regularized Dual Averaging Methods for Stochastic Optimization

Xi Chen, Qihang Lin, Javier Pena

Minimization of Continuous Bethe Approximations: A Positive Variation

Jason Pacheco, Erik B. Sudderth

Shifting Weights: Adapting Object Detectors from Image to Video

Kevin Tang, Vignesh Ramanathan, Li Fei-fei, Daphne Koller

Compressive neural representation of sparse, high-dimensional probabilities

Zachary Pitkow

Perfect Dimensionality Recovery by Variational Bayesian PCA

Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. D. Babacan

Analog readout for optical reservoir computers

Anteo Smerieri, François Duport, Yvon Paquot, Benjamin Schrauwen, Marc Haelterman

Classification Calibration Dimension for General Multiclass Losses

Harish G. Ramaswamy, Shivani Agarwal

Predicting Action Content On-Line and in Real Time before Action Onset – an Intracranial Human Study

Uri Maoz, Shengxuan Ye, Ian Ross, Adam Mamelak, Christof Koch

Proper losses for learning from partial labels

Jesús Cid-sueiro

Persistent Homology for Learning Densities with Bounded Support

Florian T. Pokorny, Hedvig Kjellström, Danica Kragic, Carl Ek

A Simple and Practical Algorithm for Differentially Private Data Release

Moritz Hardt, Katrina Ligett, Frank Mcsherry

Supervised Learning with Similarity Functions

Purushottam Kar, Prateek Jain

Accelerated Training for Matrix-norm Regularization: A Boosting Approach

Xinhua Zhang, Dale Schuurmans, Yaoliang Yu, Yao-Liang Yu

On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization

Andre Barreto, Doina Precup, Joelle Pineau

Clustering Sparse Graphs

Yudong Chen, Sujay Sanghavi, Huan Xu

Multiclass Learning with Simplex Coding

Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco, Jean-jeacques Slotine

Coupling Nonparametric Mixtures via Latent Dirichlet Processes

Dahua Lin, John W. Fisher

3D Social Saliency from Head-mounted Cameras

Hyun S. Park, Eakta Jain, Yaser Sheikh

Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics

Ashwini Shukla, Aude Billard

Dynamical And-Or Graph Learning for Object Shape Modeling and Detection

Xiaolong Wang, Liang Lin

Multiclass Learning Approaches: A Theoretical Comparison with Implications

Amit Daniely, Sivan Sabato, Shai S. Shwartz

How They Vote: Issue-Adjusted Models of Legislative Behavior

Sean Gerrish, David M. Blei

Nonconvex Penalization Using Laplace Exponents and Concave Conjugates

Zhihua Zhang, Bojun Tu

A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation

Cho-jui Hsieh, Arindam Banerjee, Pradeep K Ravikumar, Inderjit S Dhillon, Inderjit S. Dhillon

Convergence and Energy Landscape for Cheeger Cut Clustering

Xavier Bresson, Thomas Laurent, David Uminsky, James V. Brecht

A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes

Thomas Furmston, David Barber

Multi-Task Averaging

Sergey Feldman, Maya Gupta, Bela Frigyik

Kernel Hyperalignment

Alexander Lorbert, Peter J. Ramadge

A Bayesian Approach for Policy Learning from Trajectory Preference Queries

Aaron Wilson, Alan Fern, Prasad Tadepalli

Discriminatively Trained Sparse Code Gradients for Contour Detection

Ren Xiaofeng, Liefeng Bo

The Perturbed Variation

Maayan Harel, Shie Mannor

A Spectral Algorithm for Latent Dirichlet Allocation

Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-kai Liu

Multi-criteria Anomaly Detection using Pareto Depth Analysis

Ko-jen Hsiao, Kevin Xu, Jeff Calder, Alfred O. Hero

Human memory search as a random walk in a semantic network

Joseph L. Austerweil, Joshua T. Abbott, Thomas L. Griffiths

Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions

Jaedeug Choi, Kee-eung Kim

Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints

Stefan Habenschuss, Johannes Bill, Bernhard Nessler

Deep Learning of Invariant Features via Simulated Fixations in Video

Will Zou, Shenghuo Zhu, Kai Yu, Andrew Y. Ng

Distributed Non-Stochastic Experts

Varun Kanade, Zhenming Liu, Bozidar Radunovic

A dynamic excitatory-inhibitory network in a VLSI chip for spiking information reregistrations

Juan Huo

On Multilabel Classification and Ranking with Partial Feedback

Claudio Gentile, Francesco Orabona

Learning Invariant Representations of Molecules for Atomization Energy Prediction

Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler

Convex Multi-view Subspace Learning

Martha White, Xinhua Zhang, Dale Schuurmans, Yaoliang Yu, Yao-Liang Yu

Learning Mixtures of Tree Graphical Models

Anima Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade

Searching for objects driven by context

Bogdan Alexe, Nicolas Heess, Yee W. Teh, Vittorio Ferrari

Graphical Models via Generalized Linear Models

Eunho Yang, Genevera Allen, Zhandong Liu, Pradeep K Ravikumar, Pradeep K. Ravikumar

Learning visual motion in recurrent neural networks

Marius Pachitariu, Maneesh Sahani

Proximal Newton-type methods for convex optimization

Jason Lee, Yuekai Sun, Michael Saunders

Recovery of Sparse Probability Measures via Convex Programming

Mert Pilanci, Laurent E. Ghaoui, Venkat Chandrasekaran

Topic-Partitioned Multinetwork Embeddings

Peter Krafft, Juston Moore, Bruce Desmarais, Hanna M. Wallach

Efficient high dimensional maximum entropy modeling via symmetric partition functions

Paul Vernaza, Drew Bagnell

Timely Object Recognition

Sergey Karayev, Tobias Baumgartner, Mario Fritz, Trevor Darrell

Bayesian estimation of discrete entropy with mixtures of stick-breaking priors

Evan Archer, ll Memming Park, Jonathan W Pillow, Jonathan W. Pillow

A latent factor model for highly multi-relational data

Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski

Learning Image Descriptors with the Boosting-Trick

Tomasz Trzcinski, Mario Christoudias, Vincent Lepetit, Pascal Fua

Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders

Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva

Truncation-free Online Variational Inference for Bayesian Nonparametric Models

Chong Wang, David M. Blei

Privacy Aware Learning

Martin J. Wainwright, Michael I. Jordan, John C. Duchi

Factoring nonnegative matrices with linear programs

Ben Recht, Christopher Re, Joel Tropp, Victor Bittorf

Learning Label Trees for Probabilistic Modelling of Implicit Feedback

Andriy Mnih, Yee W. Teh

Bayesian nonparametric models for bipartite graphs

Francois Caron

Super-Bit Locality-Sensitive Hashing

Jianqiu Ji, Jianmin Li, Shuicheng Yan, Bo Zhang, Qi Tian

Probabilistic Event Cascades for Alzheimer's disease

Jonathan Huang, Daniel Alexander

Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss

Zhuo Wang, Alan Stocker, Daniel D. Lee, Daniel D Lee

Practical Bayesian Optimization of Machine Learning Algorithms

Jasper Snoek, Hugo Larochelle, Ryan P. Adams

Selective Labeling via Error Bound Minimization

Quanquan Gu, Tong Zhang, Jiawei Han, Chris H. Ding

The Bethe Partition Function of Log-supermodular Graphical Models

Nicholas Ruozzi

FastEx: Hash Clustering with Exponential Families

Amr Ahmed, Sujith Ravi, Alex J. Smola, Shravan M. Narayanamurthy

Clustering Aggregation as Maximum-Weight Independent Set

Nan Li, Longin J. Latecki

Topology Constraints in Graphical Models

Marcelo Fiori, Pablo Musé, Guillermo Sapiro