- Machine Learning for Big Data in the CloudAuthors: Carlos Guestrin
- High-dimensional Sampling AlgorithmsAuthors: Santosh Vempala
- Acoustic Modeling and Deep LearningAuthors: Vincent Vanhoucke

Deep Learning 1

- On autoencoder scoringAuthors: Hanna Kamyshanska; Roland Memisevic
- On the difficulty of training Recurrent Neural NetworksAuthors: Razvan Pascanu; Tomas Mikolov; Yoshua Bengio
- Maxout NetworksAuthors: Ian Goodfellow; David Warde-Farley; Mehdi Mirza; Aaron Courville; Yoshua Bengio
- Collaborative hyperparameter tuningAuthors: R
- Learning mid-level representations of objects by harnessing the aperture problemAuthors: Roland Memisevic; Georgios Exarchakis
- Approximation properties of DBNs with binary hidden units and real-valued visible unitsAuthors: Oswin Krause; Asja Fischer; Tobias Glasmachers; Christian Igel
- Better Mixing via Deep RepresentationsAuthors: Yoshua Bengio; Gregoire Mesnil; Yann Dauphin; Salah Rifai
- Fast dropout trainingAuthors: Sida Wang; Christopher Manning

Track A: Online Learning 2

- Optimal Regret Bounds for Selecting the State Representation in Reinforcement LearningAuthors: Odalric-Ambrym Maillard; Phuong Nguyen; Ronald Ortner; Daniil Ryabko
- Combinatorial Multi-Armed Bandit: General Framework, Results and ApplicationsAuthors: Wei Chen; Yajun Wang; Yang Yuan
- Dynamical Models and tracking regret in online convex programmingAuthors: Eric Hall; Rebecca Willett
- Better Rates for Any Adversarial Deterministic MDPsAuthors: Ofer Dekel; Elad Hazan
- Multiple Identifications in Multi-Armed BanditsAuthors: Sebastian Bubeck; Tengyao Wang; Nitin Viswanathan
- Gossip-based distributed stochastic bandit algorithmsAuthors: Balazs Szorenyi; Robert Busa-Fekete; Istvan Hegedus; Robert Ormandi; Mark Jelasity; Balazs Kegl
- Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier MethodAuthors: Taiji Suzuki

Track A: Crowd Sourcing and Large Scale Learning

- Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in CrowdsourcingAuthors: Xi Chen; Qihang Lin; Dengyong Zhou
- Quantile Regression for Large-scale ApplicationsAuthors: Jiyan Yang; Xiangrui Meng; Michael Mahoney
- Distributed Training of Large-scale Logistic Models,Authors: Siddharth Gopal; Yiming Yang
- Label Partitioning For Sublinear Ranking,Authors: Jason Weston; Ameesh Makadia; Hector Yee
- Human BoostingAuthors: Harsh Pareek; Pradeep Ravikumar
- Large-Scale Learning with Less RAM via RandomizationAuthors: Daniel Golovin; D. Sculley; Brendan McMahan; Michael Young
- Robust Regression on MapReduceAuthors: Xiangrui Meng; Micheal W. Mahoney
- Adaptive Task Assignment for Crowdsourced ClassificationAuthors: Chien-Ju Ho; Shahin Jabbari; Jennifer Wortman Vaughan

Compressed Sensing 1

- Feature Selection in High-Dimensional ClassificationAuthors: Mladen Kolar; Han Liu
- Exact Rule Learning via Boolean Compressed SensingAuthors: Dmitry Malioutov; Kush Varshney
- Sparse Recovery under Linear TransformationAuthors: Ji Liu; Lei Yuan; Jieping Ye
- Noisy and Missing Data Regression: Distribution-Oblivious Support RecoveryAuthors: Yudong Chen; Constantine Caramanis

Track B: Structured Labeling

- Learning from Human-Generated ListsAuthors: Kwang-Sung Jun; Jerry Zhu; Burr Settles; Timothy Rogers
- A Structural SVM Based Approach for Optimizing Partial AUCAuthors: Harikrishna Narasimhan; Shivani Agarwal
- A Machine Learning Framework for Programming by ExampleAuthors: Aditya Menon; Omer Tamuz; Sumit Gulwani; Butler Lampson; Adam Kalai
- Convex Adversarial Collective ClassificationAuthors: Mohamad Ali Torkamani; Daniel Lowd
- Learning Convex QP Relaxations for Structured PredictionAuthors: Jeremy Jancsary; Sebastian Nowozin; Carsten Rother
- Fixed-Point Model For Structured LabelingAuthors: Quannan Li; Jingdong Wang; David Wipf; Zhuowen Tu
- A Generalized Kernel Approach to Structured Output LearningAuthors: Hachem Kadri; Mohammad Ghavamzadeh; Philippe Preux
- Optimizing the F-measure in Multi-label Classification: Plug-in Rule Approach versus Structured Loss MinimizationAuthors: Krzysztof Dembczynski; Wojciech Kotlowski; Arkadiusz Jachnik; Willem Waegeman; Eyke Huellermeier

Track B: Kernel Methods

- Fastfood - Computing Hilbert Space Expansions in loglinear timeAuthors: Quoc Le; Tamas Sarlos; Alexander Smola
- Reproducing kernel Hilbert spaces are not closed under many operationsAuthors:
- Domain Adaptation under Target and Conditional Shift,Authors: Kun Zhang; Bernhard Schoelkopf; Krikamol Muandet; Zhikun Wang
- Learning Optimally Sparse Support Vector MachinesAuthors: Andrew Cotter; Shai Shalev-Shwartz; Nati Srebro
- A New Frontier of Kernel Design for Structured Data,Authors: Kilho Shin
- Characterizing the Representer TheoremAuthors: Yaoliang Yu; Hao Cheng; Dale Schuurmans; Csaba Szepesvari
- Covariate Shift in Hilber Space: A Solution Via Sorrogate KernelsAuthors: Kai Zhang; Vincent Zheng; QIaojun Wang; James Kwok; Qiang Yang

Reinforcement Learning 1

- Learning Policies for Contextual Submodular PredictionAuthors: Stephane Ross; Jiaji Zhou; Yisong Yue; Debadeepta Dey; Drew Bagnell
- Learning an Internal Dynamics Model from Control DemonstrationAuthors: Matthew Golub; Steven Chase; Byron Yu
- Safe Policy IterationAuthors: Matteo Pirotta; Marcello Restelli; Alessio Pecorino; Daniele Calandriello
- Temporal Difference Methods for the Variance of the Reward To GoAuthors: Aviv Tamar; Dotan Di Castro; Shie Mannor
- Value Iteration with incremental representation learning for continuous POMDPsAuthors: Sebastian Brechtel; Tobias Gindele; R diger Dillmann
- The Sample-Complexity of General Reinforcement LearningAuthors: Tor Lattimore; Marcus Hutter; Peter Sunehag
- Online Feature Selection for Model-based Reinforcement LearningAuthors: Trung Nguyen; Zhuoru Li; Tomi Silander; Tze Yun Leong
- Bayesian Learning of Recursively Factored EnvironmentsAuthors: Marc Bellemare; Joel Veness; Michael Bowling

Track C: Dimensionality Reduction

- Principal Component Analysis on non-Gaussian Dependent DataAuthors: Fang Han; Han Liu
- Deep Canonical Correlation AnalysisAuthors: Galen Andrew; Jeff Bilmes; Raman Arora; Karen Livescu
- Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target AlignmentAuthors: Billy Chang; Uwe Kruger; Rafal Kustra; Junping Zhang
- Vanishing Component AnalysisAuthors: Roi Livni; David Lehavi; Sagi Schein; Hila Nachliely; Shai Shalev-Shwartz; Amir Globerson
- Fast algorithms for sparse principal component analysis based on Rayleigh quotient iterationAuthors: Volodymyr Kuleshov
- Efficient Dimensionality Reduction for Canonical Correlation AnalysisAuthors: Haim Avron; Christos Boutsidis ; Sivan Toledo ; Anastasios Zouzias
- Adaptive Sparsity in Gaussian Graphical ModelsAuthors: Eleanor Wong; Suyash Awate; P. Thomas Fletcher
- The Most Generative Maximum Margin Bayesian NetworksAuthors: Robert Peharz; Sebastian Tschiatschek; Franz Pernkopf

Track D: Learning Theory 3

- Activized Learning with Uniform Classification NoiseAuthors: Liu Yang; Steve Hanneke
- Efficient Active Learning of Halfspaces: an Aggressive ApproachAuthors: Alon Gonen; Sivan Sabato; Shai Shalev-Shwartz
- Selective sampling algorithms for cost-sensitive multiclass predictionAuthors: Alekh Agarwa
- Generic Exploration and K-armed Voting BanditsAuthors: Tanguy Urvoy; Fabrice Clerot; Raphael Feraud; Sami Naamane
- Efficient Semi-supervised and Active Learning of DisjunctionsAuthors: Maria-Florina Belcan; Christopher Berlind; Steven Ehrlich; Yingyu Liang
- Cost-sensitive Multiclass Classification Risk BoundsAuthors: Bernardo Pires; Csaba Szepesvari; Mohammad Ghavamzadeh
- Active Learning for Multi-Objective OptimizationAuthors: Marcela Zuluaga; Guillaume Sergent; Andreas Krause; Markus Pueschel
- Near-optimal Batch Mode Active Learning and Adaptive Submodular OptimizationAuthors: Yuxin Chen; Andreas Krause

Social Networks

- Copy or Coincidence? A Model for Detecting Social Influence and Duplication EventsAuthors: Lisa Friedland; David Jensen; Michael Lavine
- Mixture of Mutually Exciting Processes for Viral DiffusionAuthors: Shuang-Hong Yang; Hongyuan Zha
- Dynamic Probabilistic Models for Latent Feature Propagation in Social NetworksAuthors: Creighton Heaukulani; Ghahramani Zoubin
- Modeling Information Propagation with Survival TheoryAuthors: Manuel Gomez-Rodriguez; Jure Leskovec; Bernhard Sch
- Learning Triggering Kernels for Multi-dimensional Hawkes ProcessesAuthors: Ke Zhou; Le Song; Hongyuan Zha
- Causal Estimation of Peer Influence EffectsAuthors: Edward Kao; Panos Toulis; Edoardo Airoldi; Donald Rubin
- Modeling Temporal Evolution and Multiscale Structure in NetworksAuthors: Tue Herlau; Morten M
- Scalable Optimization of Neighbor Embedding for VisualizationAuthors: Zhirong Yang; Jaakko Peltonen; Samuel Kaski

Track D: Statistical Methods

- Computation-Risk Tradeoffs for Covariance-Thresholded RegressionAuthors: Dinah Shender; John Lafferty
- Scalable Simple Random Sampling and Stratified SamplingAuthors: Xiangrui Meng
- The lasso, persistence, and cross-validationAuthors: Darren Homrighausen; Daniel McDonald
- Consistency versus Realizable H-Consistency for Multiclass ClassificationAuthors: Phil Long; Rocco Servedio
- Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon EntropyAuthors: Jean Honorio; Jaakkola Tommi
- Scale Invariant Conditional Dependence MeasuresAuthors: Sashank J Reddi; Barnabas Poczos
- Infinite Markov-Switching Maximum Entropy Discrimination MachinesAuthors: Sotirios Chatzis
- Distribution to Distribution Regression,Authors: Junier Oliva; Barnabas Poczos; Jeff Schneide

Track C: Matrix Factorization

- Fast Conical Hull Algorithms for Near-separable Non-negative Matrix FactorizationAuthors: Abhishek Kumar; Vikas Sindhwani; Prabhanjan Kambadur
- General Functional Matrix Factorization Using Gradient BoostingAuthors: Tianqi Chen; Hang Li; Qiang Yang; Yong Yu
- Fast Max-Margin Matrix Factorization with Data AugmentationAuthors: Minjie Xu; Jun Zhu; Bo Zhang
- Local Low-Rank Matrix Approximation,Authors: Joonseok Lee; Seungyeon Kim; Guy Lebanon; Yoram Singer
- Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization ModelsAuthors: Umut Simsekli; Yusuf Kenan Yilmaz; Ali Taylan Cemgil
- ELLA: An Efficient Lifelong Learning AlgorithmAuthors: Paul Ruvolo; Eric Eaton
- Riemannian Similarity Learning,Authors: Li Cheng
- Multiple-Source Cross ValidationAuthors: Krzysztof Geras; Charles Sutton

Deep Learning 2

- Learning the Structure of Sum-Product NetworksAuthors: Robert Gens; Domingos Pedro
- Deep learning with COTS HPC systemsAuthors: Adam Coates; Brody Huval; Tao Wang; David Wu; Bryan Catanzaro; Ng Andrew
- Learning and Selecting Features Jointly with Point-wise Gated Boltzmann MachinesAuthors: Kihyuk Sohn; Guanyu Zhou; Chansoo Lee; Honglak Lee
- Regularization of Neural Networks using DropConnectAuthors: Li Wan; Matthew Zeiler; Sixin Zhang; Yann Le Cun; Rob Fergus
- Thurstonian Boltzmann Machines: Learning from Multiple InequalitiesAuthors: Truyen Tran; Dinh Phung; Svetha Venkatesh
- No more pesky learning ratesAuthors: Tom Schaul; Sixin Zhang; Yann LeCun
- Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision ArchitecturesAuthors: James Bergstra; Daniel Yamins; David Cox

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