Papers
Hierarchical Regularization Cascade for Joint Learning
Alon Zweig, Daphna Weinshall
The Sample-Complexity of General Reinforcement Learning
Tor Lattimore, Marcus Hutter, Peter Sunehag
Gossip-based distributed stochastic bandit algorithms
Balazs Szorenyi, Robert Busa-Fekete, Istvan Hegedus et al.
Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning
Gang Niu, Wittawat Jitkrittum, Bo Dai et al.
Guided Policy Search
Sergey Levine, Vladlen Koltun
Activized Learning with Uniform Classification Noise
Liu Yang, Steve Hanneke
Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data
Jan-Willem Meent, Jonathan Bronson, Frank Wood et al.
Sparse coding for multitask and transfer learning
Andreas Maurer, Massi Pontil, Bernardino Romera-Paredes
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization
Stefano Ermon, Carla Gomes, Ashish Sabharwal et al.
Large-Scale Learning with Less RAM via Randomization
Daniel Golovin, D. Sculley, Brendan McMahan et al.
Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment
Billy Chang, Uwe Kruger, Rafal Kustra et al.
Margins, Shrinkage, and Boosting
Matus Telgarsky
An Adaptive Learning Rate for Stochastic Variational Inference
Rajesh Ranganath, Chong Wang, Blei David et al.
Distributed training of Large-scale Logistic models
Siddharth Gopal, Yiming Yang
A Practical Algorithm for Topic Modeling with Provable Guarantees
Sanjeev Arora, Rong Ge, Yonatan Halpern et al.
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions
Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher
Exploring the Mind: Integrating Questionnaires and fMRI
Esther Salazar, Ryan Bogdan, Adam Gorka et al.
Subtle Topic Models and Discovering Subtly Manifested Software Concerns Automatically
Mrinal Das, Suparna Bhattacharya, Chiranjib Bhattacharyya et al.
Modeling Musical Influence with Topic Models
Uri Shalit, Daphna Weinshall, Gal Chechik
Sparse projections onto the simplex
Anastasios Kyrillidis, Stephen Becker, Volkan Cevher et al.
Sequential Bayesian Search
Zheng Wen, Branislav Kveton, Brian Eriksson et al.
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines
Kihyuk Sohn, Guanyu Zhou, Chansoo Lee et al.
SADA: A General Framework to Support Robust Causation Discovery
Ruichu Cai, Zhenjie Zhang, Zhifeng Hao
Collaborative hyperparameter tuning
Rémi Bardenet, Mátyás Brendel, Balázs Kégl et al.