An Optimal Policy for Target Localization with Application to Electron Microscopy Raphael Sznitman, Aurelien Lucchi, Peter Frazier, Bruno Jedynak, Pascal Fua
abstract/pdf
Domain Generalization via Invariant Feature Representation Krikamol Muandet, David Balduzzi, Bernhard Schoelkopf
abstract/pdf/supplementary
A Spectral Learning Approach to Range-Only SLAM Byron Boots, Geoff Gordon
abstract/pdf/supplementary
Near-Optimal Bounds for Cross-Validation via Loss Stability Ravi Kumar, Daniel Lokshtanov, Sergei Vassilvitskii, Andrea Vattani
abstract/pdf
Sparsity-Based Generalization Bounds for Predictive Sparse Coding Nishant Mehta, Alexander Gray
abstract/pdf/supplementary
Sparse Uncorrelated Linear Discriminant Analysis Xiaowei Zhang, Delin Chu
abstract/pdf
Block-Coordinate Frank-Wolfe Optimization for Structural SVMs Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher
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Fast Probabilistic Optimization from Noisy Gradients Philipp Hennig
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Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir, Tong Zhang abstract/pdf
Stochastic Alternating Direction Method of Multipliers Hua Ouyang, Niao he, Long Tran, Alexander Gray
abstract/pdf/supplementary
Noisy Sparse Subspace Clustering Yu-Xiang Wang, Huan Xu
abstract/pdf/supplementary
Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models Sinead Williamson, Avinava Dubey, Eric Xing
abstract/pdf/supplementary
Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction Sébastien Giguère, François Laviolette, Mario Marchand, Khadidja Sylla
abstract/pdf/supplementary
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures James Bergstra, Daniel Yamins, David Cox
abstract/pdf
Gibbs Max-Margin Topic Models with Fast Sampling Algorithms Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang
abstract/pdf
Cost-Sensitive Tree of Classifiers Zhixiang Xu, Matt Kusner, Kilian Weinberger, Minmin Chen
abstract/pdf
Learning Hash Functions Using Column Generation Xi Li, Guosheng Lin, Chunhua Shen, Anton van den Hengel, Anthony Dick
abstract/pdf
Combinatorial Multi-Armed Bandit: General Framework, Results and Applications Wei Chen, Yajun Wang, Yang Yuan
abstract/pdf/supplementary
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization Yuxin Chen, Andreas Krause
abstract/pdf/supplementary
Convex formulations of radius-margin based Support Vector Machines Huyen Do, Alexandros Kalousis
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Modelling Sparse Dynamical Systems with Compressed Predictive State Representations William Hamilton, Mahdi Milani Fard, Joelle Pineau
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A Machine Learning Framework for Programming by Example Aditya Menon, Omer Tamuz, Sumit Gulwani, Butler Lampson, Adam Kalai
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Discriminatively Activated Sparselets Ross Girshick, Hyun Oh Song, Trevor Darrell
abstract/pdf/supplementary
The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification Ofir Pele, Ben Taskar, Amir Globerson, Michael Werman
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Fixed-Point Model For Structured Labeling Quannan Li, Jingdong Wang, David Wipf, Zhuowen Tu a
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Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation Boqing Gong, Kristen Grauman, Fei Sha
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Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur a
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Principal Component Analysis on non-Gaussian Dependent Data Fang Han, Han Liu
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Learning Linear Bayesian Networks with Latent Variables Animashree Anandkumar, Daniel Hsu, Adel Javanmard, Sham Kakade
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Multiple Identifications in Multi-Armed Bandits Sebastian Bubeck, Tengyao Wang, Nitin Viswanathan
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Learning Optimally Sparse Support Vector Machines Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro
abstract/pdf/supplementary
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks Creighton Heaukulani, Ghahramani Zoubin
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Efficient Sparse Group Feature Selection via Nonconvex Optimization Shuo Xiang, Xiaoshen Tong, Jieping Ye
abstract/pdf/supplementary
Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation Model Min Xiao, Yuhong Guo
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Maximum Variance Correction with Application to A* Search Wenlin Chen, Kilian Weinberger, Yixin Chen
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Adaptive Sparsity in Gaussian Graphical Models Eleanor Wong, Suyash Awate, P. Thomas Fletcher
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Average Reward Optimization Objective In Partially Observable Domains Yuri Grinberg, Doina Precup
abstract/pdf/supplementary
Feature Selection in High-Dimensional Classification Mladen Kolar, Han Liu
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Human Boosting Harsh Pareek, Pradeep Ravikumar
abstract/pdf/supplementary
Efficient Dimensionality Reduction for Canonical Correlation Analysis Haim Avron, Christos Boutsidis, Sivan Toledo, Anastasios Zouzias
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Parsing epileptic events using a Markov switching process model for correlated time series Drausin Wulsin, Emily Fox, Brian Litt
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Optimal rates for stochastic convex optimization under Tsybakov noise condition Aaditya Ramdas, Aarti Singh a
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A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning Arash Afkanpour, Andras Gyorgy, Csaba Szepesvari, Michael Bowling abstract/pdf
Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery Yudong Chen, Constantine Caramanis
abstract/pdf/supplementary
Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier Method Taiji Suzuki
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A New Frontier of Kernel Design for Structured Data Kilho Shin
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Learning with Marginalized Corrupted Features Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Weinberger
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Approximation properties of DBNs with binary hidden units and real-valued visible units Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel abstract/pdf
Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization Martin Jaggi
abstract/pdf/supplementary
General Functional Matrix Factorization Using Gradient Boosting Tianqi Chen, Hang Li, Qiang Yang, Yong Yu
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Iterative Learning and Denoising in Convolutional Neural Associative Memories Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi abstract/pdf/supplementary
Scaling Multidimensional Gaussian Processes using Projected Additive Approximations Elad Gilboa, Yunus Saatci, John Cunningham abstract/pdf/supplementary
Active Learning for Multi-Objective Optimization Marcela Zuluaga, Guillaume Sergent, Andreas Krause, Markus Pueschel
abstract/pdf/supplementary
A Generalized Kernel Approach to Structured Output Learning Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux
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Efficient Active Learning of Halfspaces: an Aggressive Approach Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz
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Enhanced statistical rankings via targeted data collection Braxton Osting, Christoph Brune, Stanley Osher
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Online Feature Selection for Model-based Reinforcement Learning Trung Nguyen, Zhuoru Li, Tomi Silander, Tze Yun Leong
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ELLA: An Efficient Lifelong Learning Algorithm Paul Ruvolo, Eric Eaton
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A Structural SVM Based Approach for Optimizing Partial AUC Harikrishna Narasimhan, Shivani Agarwal
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Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs Sesh Kumar K. S., Francis Bach
abstract/pdf/supplementary
Adaptive Task Assignment for Crowdsourced Classification Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
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Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko
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Better Mixing via Deep Representations Yoshua Bengio, Gregoire Mesnil, Yann Dauphin, Salah Rifai
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Online Latent Dirichlet Allocation with Infinite Vocabulary Ke Zhai, Jordan Boyd-Graber
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Characterizing the Representer Theorem Yaoliang Yu, Hao Cheng, Dale Schuurmans, Csaba Szepesvari
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Dynamical Models and tracking regret in online convex programming Eric Hall, Rebecca Willett a
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Large-Scale Bandit Problems and KWIK Learning Jacob Abernethy, Kareem Amin, Michael Kearns, Moez Draief
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Vanishing Component Analysis Roi Livni, David Lehavi, Sagi Schein, Hila Nachliely, Shai Shalev-Shwartz, Amir Globerson
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Learning an Internal Dynamics Model from Control Demonstration Matthew Golub, Steven Chase, Byron Yu
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Robust Structural Metric Learning Daryl Lim, Gert Lanckriet, Brian McFee
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Constrained fractional set programs and their application in local clustering and community detection Thomas Bühler, Shyam Sundar Rangapuram, Simon Setzer, Matthias Hein
abstract/pdf/supplementary
Efficient Semi-supervised and Active Learning of Disjunctions Nina Balcan, Christopher Berlind, Steven Ehrlich, Yingyu Liang
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Convex Adversarial Collective Classification Mohamad Ali Torkamani, Daniel Lowd
abstract/pdf/supplementary
Rounding Methods for Discrete Linear Classification Yann Chevaleyre, Frederick Koriche, Jean-Daniel Zucker
abstract/pdf/supplementary
Mixture of Mutually Exciting Processes for Viral Diffusion Shuang-Hong Yang
Gaussian Process Vine Copulas for Multivariate Dependence David Lopez-Paz, Jose Miguel Hernandez-Lobato, Ghahramani Zoubin
Stochastic Simultaneous Optimistic Optimization Michal Valko, Alexandra Carpentier, Remi Munos
Toward Optimal Stratification for Stratified Monte-Carlo Integration Alexandra Carpentier, Remi Munos
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems Pinghua Gong, Jieping Ye, Changshui Zhang
Thurstonian Boltzmann Machines: Learning from Multiple Inequalities Truyen Tran, Dinh Phung, Svetha Venkatesh
A Variational Approximation for Topic Modeling of Hierarchical Corpora Do-kyum Kim, Geoffrey Voelker, Lawrence Saul
Forecastable Component Analysis (ForeCA) Georg Goerg
Ellipsoidal Multiple Instance Learning Gabriel Krummenacher, Cheng Soon Ong, Joachim Buhmann
Local Low-Rank Matrix Approximation Joonseok Lee, Seungyeon Kim, Guy Lebanon, Yoram Singer
Generic exploration and K-armed voting bandits Tanguy Urvoy, Fabrice Clerot, Raphael Feraud, Sami Naamane
A unifying framework for vector-valued manifold regularization and multi-view learning Minh Ha Quang, Loris Bazzani, Vittorio Murino
Learning Connections in Financial Time Series Gartheeban Ganeshapillai, John Guttag, Andrew Lo
Fast dropout training Sida Wang
Scalable Optimization for Neighbor Embedding for Visualization Zhirong Yang, Jaakko Peltonen, Samuel Kaski
Precision-recall space to correct external indices for biclustering Blaise Hanczar, Mohamed Nadif
Monochromatic Bi-Clustering Shai Ben-David, Sharon Wulff, Ruth Urner
Gated Autoencoders with Tied Input Weights Alain Droniou, Olivier Sigaud
Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings Nicola Rebagliati
Transition Matrix Estimation in High Dimensional Vector Autoregressive Models Fang Han, Han Liu
Label Partitioning For Sublinear Ranking Jason Weston, Ameesh Makadia, Hector Yee
Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing Huayan Wang, Koller Daphne
Collaborative hyperparameter tuning Rémi Bardenet, Mátyás Brendel, Balazs Kegl, Michele Sebag
SADA: A General Framework to Support Robust Causation Discovery Ruichu Cai, Zhenjie Zhang, Zhifeng Hao
Jointly Learning and Selecting Features via Conditional Point-wise Mixture RBMs Kihyuk Sohn, Honglak Lee
Sequential Bayesian Search Zheng Wen, Branislav Kveton, Brian Eriksson, Sandilya Bhamidipati
Sparse projections onto the simplex Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch
Modeling Musical Influence with Topic Models Uri Shalit, Daphna Weinshall, Gal Chechik
Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically Mrinal Das, Suparna Bhattacharya, Chiranjib Bhattacharyya, Gopinath Kanchi
Exploring the Mind: Integrating Questionnaires and fMRI Esther Salazar, Ahmad Hariri, Lawrence Carin
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher
A Practical Algorithm for Topic Modeling with Provable Guarantees Sanjeev Arora, Rong Ge, Yonatan Halpern, David Mimno, Ankur Moitra, David Sontag, Michael Zhu
Distributed training of large-scale logistic models Siddharth Gopal, Yiming Yang
An Adaptive Learning Rate for Stochastic Variational Inference Rajesh Ranganath, Chong Wang, Blei David, Eric Xing
Margins, Shrinkage, and Boosting Matus Telgarsky
Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment Billy Chang, Uwe Kruger, Rafal Kustra
Large-Scale Learning with Less RAM via Randomization D. Sculley, Daniel Golovin, Brendan McMahan, Michael Young
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization Stefano Ermon, Carla Gomes, Ashish Sabharwal, Bart Selman
Sparse coding for multitask and transfer learning Andreas Maurer, Massi Pontil, Bernardino Romera-Paredes
Direct Modeling of Complex Invariances in Visual Object Features Ka YU Hui
Learning biochemical kinetic models from single-molecule data with hierarchically-coupled hidden Markov models Jan-Willem Van de Meent, Jonathan Bronson, Ruben Gonzalez, Chris Wiggins
Activized Learning with Uniform Classification Noise Liu Yang, Steve Hanneke
Guided Policy Search Levine, Sergey
Squared-loss Mutual Information Regularization Niu, Gang
Gossip-based distributed stochastic bandit algorithms Busa-Fekete, Robert
The Sample-Complexity of General Reinforcement Learning Lattimore, Tor
Hierarchical Regularization Cascade for Joint Learning Zweig, Alon
Multi-Class Classification with Maximum Margin Multiple Kernel Rostamizadeh, Afshin
Bayesian Games for Adversarial Regression Problems Großhans, Michael
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing Chen, Xi
Markov Network Estimation From Multi-attribute Data Kolar, Mladen
MILEAGE: Multiple Instance LEArning with Global Embedding Zhang, Dan
Sparse Recovery under Linear Transformation Liu, Ji
Learning mid-level representations of objects by harnessing the aperture problem Memisevic, Roland
Efficient Ranking from Pairwise Comparisons Wauthier, Fabian
Differentially Private Learning with Kernels Jain, Prateek
Thompson Sampling for Contextual Bandits with Linear Payoffs Agrawal, Shipra
Clustering and Learning Behaviors using a Sparse Latent Space Montesano, Lui
Inference algorithms for pattern-based CRFs on sequence data Takhanov, Rustem
One-Bit Compressed Sensing: Provable Support and Vector Recovery Jain, Prateek
Tensor Analyzers Tang, Yichuan
Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression Hocking, Toby
Learning from Human List Production Jun, Kwang-Sung
A Fast and Exact Energy Minimization Algorithm for Cycle MRFs Wang, Huayan
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning Tarlow, Daniel
An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation Bryan, Nicholas
Estimating Unknown Sparsity in Compressed Sensing Lopes, Miles
MAD-Bayes: MAP-based Asymptotic Derivations from Bayes Broderick, Tamara
The Most Generative Maximum Margin Bayesian Networks Peharz, Robert
Fastfood – Computing Hilbert Space Expansions in loglinear time Smola, Alexander
Causal Estimation of Peer Influence Effects Kao, Edward
Joint Transfer and Batch-mode Active Learning Chattopadhyay, Rita
Relaxed expectation propagation based on $l_1$-penalized KL minimization Qi, Yuan
Mean Reversion with a Variance Threshold Cuturi, Marco
Top-down particle filtering for Bayesian decision trees Lakshminarayanan, Balaji
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations Balasubramanian, Krishnakumar
Can We Recognize Tiger by Bus Images? — Robust and Discriminative Self-Taught Image Categorization Wang, Hua
Safe Policy Iteration Restelli, Marcello
Unfolding Latent Tree Structures using 4th Order Tensors Ishteva, Mariya
Learning Fair Representations Zemel, Rich
Hierarchical Tensor Decomposition of Latent Tree Graphical Models Song, Le
No more pesky learning rates Schaul, Tom
Multi-View Clustering and Feature Learning via Structured Sparsity Wang, Hua
Planning by Prioritized Sweeping with Small Backups van Seijen, Harm
Value Iteration with incremental representation learning for continuous POMDPs Brechtel, Sebastian
Learning Heteroscedastic Models by Convex Programming under Group Sparsity Dalalyan, Arnak
Covariate Shift in Hilber Space: A Solution Via Sorrogate Kernels Zhang, Kai
A Local Algorithm for Finding Well-Connected Clusters Zhu, Zeyuan Allen
Efficient Multi-label Classification with Many Labels Bi, Wei
Spectral Compressed Sensing via Structured Matrix Completion Chen, Yuxin
Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model Yang, Ming
Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images Cho, Kyunghyun
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions Kar, Purushottam
Non-Linear Stationary Subspace Analysis with Application to Video Classification Baktashmotlagh, Mahsa
Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy Honorio, Jean
That was fast! Speeding up NN search of high dimensional distributions. Coviello, Emanuele
Entropic Affinities: Properties and Efficient Numerical Computation Carreira-Perpinan, Miguel
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction Varma, Manik
Temporal Difference Methods for the Variance of the Reward To Go Tamar, Aviv
$\propto$SVM for Learning with Label Proportions Yu, Felix
Parameter Learning and Convergent Inference for Dense Random Fields Kraehenbuehl, Philipp
Loss-Proportional Subsampling for Subsequent ERM Mineiro, Paul
Scalable Simple Random Sampling and Stratified Sampling Meng, Xiangrui
Riemannian Similarity Learning Cheng, Li
On Compact Codes for Spatially Pooled Features Jia, Yangqing
Dynamic Covariance Models for Multivariate Financial Time Series Wu, Yue
Revisiting the Nystrom method for improved large-scale machine learning Gittens, Alex
Infinite Positive Semidefinite Tensor Factorization with Application to Music Signal Analysis Yoshii, Kazuyoshi
A Unified Robust Regression Model for Lasso-like Algorithms Yang, Wenzhuo
Quickly Boosting Decision Trees — Pruning Underachieving Features Early Appel, Ron
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance Agarwal, Shivani
Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment Chuang, Jason
Online Kernel Learning with a Near Optimal Sparsity Bound Zhang, Lijun
Spectral Learning of Hidden Markov Models from Dynamic and Static Data Huang, Tzu-Kuo
Analogy-preserving Semantic Embedding for Visual Object Categorization Hwang, Sung Ju
Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training Izbicki, Michael
Factorial Multi-Task Learning : A Bayesian Nonparametric Approach Gupta, Sunil
Modeling Information Propagation with Survival Theory Gomez-Rodriguez, Manuel
Better Rates for Any Adversarial Deterministic MDPs Hazan, Elad
ABC Reinforcement Learning Dimitrakakis, Christos
Sharp Generalization Error Bounds for Randomly-projected Classifiers Durrant, Robert
On learning parametric-output HMMs Kontorovich, Aryeh
Latent Dirichlet Allocation Topic Model with Soft Assignment of Descriptors to Words Weinshall, Daphna
On autoencoder scoring Kamyshanska, Hanna
Infinite Markov-Switching Maximum Entropy Discrimination Machines Chatzis, Sotirios
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers Morvant, Emilie
Sparse PCA through Low-rank Approximations Papailiopoulos, Dimitris
Computation-Risk Tradeoffs for Covariance-Thresholded Regression Shender, Dinah
Exact Rule Learning via Boolean Compressed Sensing Varshney, Kush
Robust Sparse Regression under Adversarial Corruption Chen, Yudong
Optimization with First-Order Surrogate Functions Mairal, Julien
Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Forecasting Koppula, Hema
Consistency versus Realizable H-Consistency for Multiclass Classification Long, Phil
Feature Multi-Selection among Subjective Features Sabato, Sivan
Domain Adaptation under Target and Conditional Shift Zhang, Kun
Collective Stability and Structured Prediction: Generalization from One Example London, Ben
Stable Coactive Learning via Perturbation Raman, Karthik
Max-Margin Multiple-Instance Dictionary Learning Tu, Zhuowen
Fast Semidifferential-based Submodular Function Optimization Jegelka, Stefanie
Kernelized Bayesian Matrix Factorization Gönen, Mehmet
Learning the Structure of Sum-Product Networks Gens, Robert
Quantile Regression for Large-scale Applications Mahoney, Michael
Robust Regression on MapReduce Mahoney, Michael
Infinitesimal Annealing for Training Semi-Supervised Support Vector Machine Takeuchi, Ichiro
One-Pass AUC Optimization Gao, Wei
Learning Convex QP Relaxations for Structured Prediction Jancsary, Jeremy
Concurrent Reinforcement Learning from Customer Interaction Sequences Silver, David
Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner Sun, Peng
Stability and Hypothesis Transfer Learning Kuzborskij, Ilja
Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models Khan, Mohammad Emtiyaz
Modeling Temporal Evolution and Multiscale Structure in Networks Herlau, Tue
Dependent Normalized Random Measures Chen, Changyou
Fast Max-Margin Matrix Factorization with Data Augmentation Xu, Minjie
Natural Image Bases to Represent Neuroimaging Data Gupta, Ashish
Breaking the Small Cluster Barrier of Graph Clustering Ailon, Nir
Approximate Inference in Collective Graphical Models Sheldon, Daniel
Scaling the Indian Buffet Process via Submodular Maximization Reed, Colorado
Mini-Batch Primal and Dual Methods for SVMs Takac, Martin
The lasso, persistence, and leave-one-out cross-validation Homrighausen, Darren
Spectral Experts for Estimating Mixtures of Linear Regressions Chaganty, Arun Tejasvi
Distribution to Distribution Regression Oliva, Junier
Regularization of Neural Networks using DropConnect Wan, Li
Gaussian Process Kernels for Pattern Discovery and Extrapolation Wilson, Andrew
Anytime Representation Learning Xu, Zhixiang
Algorithms for Direct 0–1 Loss Optimization in Binary Classification Sanner, Scott
Top-k Selection based on Adaptive Sampling of Noisy Preferences Busa-Fekete, Robert
The Extended Parameter Filter Erol, Yusuf Bugra
Exploiting Ontology Structures and Unlabeled Data for Learning Blum, Avrim
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions Zhang, Lijun
Optimizing the F-measure in Multi-label Classification: Plug-in Rule Approach versus Structured Loss Minimization Dembczynski, Krzysztof
On the importance of initialization and momentum in deep learning Sutskever, Ilya
Collaborative Filtering with Hybrid Restricted Boltzmann Machines Nakov, Preslav
Intersecting singularities for multi-structured estimation Richard, Emile
Structure Discovery in Nonparametric Regression through Compositional Kernel Search Lloyd, James
Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events Friedland, Lisa
Smooth Operators and an RKHS Integration Approach Grunewalder, Steffen
The Cross-Entropy Method Optimizes for Quantiles Goschin, Sergiu
Topic Discovery through Data Dependent and Random Projections Ding, Weicong
Bayesian Learning of Recursively Factored Environments Bellemare, Marc
Selective sampling algorithms for cost-sensitive multiclass prediction Agarwal, Alekh
The Bigraphical Lasso Kalaitzis, Alfredo
Almost Optimal Exploration in Multi-Armed Bandits Koren, Tomer
Deep Canonical Correlation Analysis Andrew, Galen
Consistency of Online Random Forests Denil, Misha
Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting Kolter, Zico
Fast Image Tagging Chen, Minmin
Expensive Function Optimization with Stochastic Binary Outcomes Tesch, Matthew
Multiple-Source Cross Validation Geras, Krzysztof
Learning Triggering Kernels for Multi-dimensional Hawkes Processes Zhou, Ke
On the difficulty of training Recurrent Neural Networks Pascanu, Razvan
Maxout Networks Goodfellow, Ian
Predictable Dual-View Hashing Rastegari, Mohammad
Deep learning with COTS HPC systems Coates, Adam
Nonparametric Mixture of Gaussian Processes with Constraints Ross, James
Scale Invariant Conditional Dependence Measures J Reddi, Sashank
Learning Policies for Contextual Submodular Prediction Ross, Stephane
Manifold Perserving Hierarchical Topic Models for Quantization and Approximation Kim, Minje
Safe Screening of Non-Support Vectors in Pathwise SVM Computation Takeuchi, Ichiro
Cost-sensitive Multiclass Classification Risk Bounds Pires, Bernardo
Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion Yi, Jinfeng
Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models Simsekli, Umut
Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration Kuleshov, Volodymyr
Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling Ahmed, Amr
Tree-Independent Dual-Tree Algorithms Curtin, Ryan
Multilinear Multitask Learning Romera-Paredes, Bernardino
Online Learning under Delayed Feedback Gyorgy, Andras
Adaptive Hamiltonian and Riemann Manifold Monte Carlo Wang, Ziyu
Coco-Q: Learning in Stochastic Games with Side Payments Hilliard, Elizabeth
On Nonlinear Generalization of Sparse Coding and Dictionary Learning Ho, Jeffrey