### Online Learning (I)

Session Chair: Sébastien Bubeck

Long talks (20 minutes + 5 minutes for questions)

- Oren Anava, Elad Hazan, Shie Mannor and Ohad Shamir.
*Online Learning for Time Series Prediction* - Lachlan Andrew, Siddharth Barman, Katrina Ligett, Minghong Lin, Adam Meyerson, Alan Roytman and Adam Wierman.
*A Tale of Two Metrics: Simultaneous Bounds on Competitiveness and Regret* - Wei Han, Alexander Rakhlin and Karthik Sridharan.
*Competing With Strategies*

Short talks (5 minutes)

- Alexander Rakhlin and Karthik Sridharan.
*Online Learning with Predictable Sequences* - Shie Mannor and Vianney Perchet.
*Approachability, fast and slow* - Peter Bartlett, Peter Grunwald, Peter Harremoes, Fares Hedayati and Wojciech Kotlowski.
*Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families*

### Online Learning (II)

Session Chair: Sasha Rakhlin

Long talks (20 minutes + 5 minutes for questions)

- Andrey Bernstein, Shie Mannor and Nahum Shimkin.
*Opportunistic Strategies for Generalized No-Regret Problems* - Luc Devroye, Gábor Lugosi and Gergely Neu.
*Prediction by random-walk perturbation* - Eyal Gofer, Nicolò Cesa-Bianchi, Claudio Gentile and Yishay Mansour.
*Regret Minimization for Branching Experts* - Claudio Gentile, Mark Herbster and Stephen Pasteris.
*Online Similarity Prediction of Networked Data from Known and Unknown Graphs*

### Bandits

Session Chair: Nicolo Cesa-Bianchi

Long talks (20 minutes + 5 minutes for questions)

- Ohad Shamir.
*On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization* - Amit Daniely and Tom Halbertal.
*The price of bandit information in multiclass online classification* - Sébastien Bubeck, Vianney Perchet and Philippe Rigollet.
*Bounded regret in stochastic multi-armed bandits* - Chao-Kai Chiang, Chia-Jung Lee and Chi-Jen Lu.
*Beating Bandits in Gradually Evolving Worlds*

Short talks (5 minutes)

- Emilie Kaufmann and Shivaram Kalyanakrishnan.
*Information Complexity in Bandit Subset Selection* - Gabor Bartok
*A near-optimal algorithm for finite partial-monitoring games against adversarial opponents* - Ittai Abraham, Omar Alonso, Vasilis Kandylas and Aleksandrs Slivkins.
*Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem*

### Computational learning theory (I)

Session Chair: Vitaly Feldman

Long talks (20 minutes + 5 minutes for questions)

- Quentin Berthet and Philippe Rigollet.
*Complexity Theoretic Lower Bounds for Sparse Principal Component Detection***(best paper)** - Daniel Kane, Adam Klivans and Raghu Meka.
*Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching*

### Computational learning theory (II)

Session Chair: Elad Hazan

Long talks (20 minutes + 5 minutes for questions)

- Vitaly Feldman, Pravesh Kothari and Jan Vondrak.
*Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees* - Sung-Soon Choi.
*Polynomial Time Optimal Query Algorithms for Finding Graphs with Arbitrary Real Weights* - Moritz Hardt and Ankur Moitra.
*Algorithms and Hardness for Robust Subspace Recovery* - Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang and Shenghuo Zhu.
*Recovering Optimal Solution by Dual Random Projection*

### Computational learning theory (III)

Session Chair: Daniel Hsu

Long talks (20 minutes + 5 minutes for questions)

- Joseph Anderson, Navin Goyal and Luis Rademacher.
*Efficient Learning of Simplices* - Sanjoy Dasgupta and Kaushik Sinha.
*Randomized partition trees for exact nearest neighbor search*

### Statistical learning theory (I)

Session Chair: Philippe Rigollet

Long talks (20 minutes + 5 minutes for questions)

- Mehrdad Mahdavi and Rong Jin.
*Passive Learning with Target Risk* - Clayton Scott, Gilles Blanchard and Gregory Handy.
*Classification with Asymmetric Label Noise: Consistency and Maximal Denoising* - Yuchen Zhang, John Duchi and Martin Wainwright.
*Divide and Conquer Kernel Ridge Regression*

Short talks (5 minutes)

- Francis Bach.
*Sharp analysis of low-rank kernel matrix approximations* - Robert Vandermeulen and Clayton Scott.
*Consistency of Robust Kernel Density Estimators* - Andreas Maurer and Massimiliano Pontil.
*Excess risk bounds for multitask learning with trace norm regularization* - Cheng Li, Wenxin Jiang and Martin Tanner.
*General Oracle Inequalities for Gibbs Posterior with Application to Classification and Ranking* - Matus Telgarsky.
*Boosting with the Logistic Loss is Consistent*

### Statistical learning theory (II)

Session Chair: Manfred Warmuth

Long talks (20 minutes + 5 minutes for questions)

- Roi Livni and Pierre Simon.
*Honest Compressions and Their Application to Compression Schemes***(Mark Fulk award)** - Abhradeep Guha Thakurta and Adam Smith.
*Differentially Private Feature Selection via Stability Arguments, and the Robustness of the Lasso*

### Active learning

Session Chair: Sanjoy Dasgupta

Long talks (20 minutes + 5 minutes for questions)

- Pranjal Awasthi, Vitaly Feldman and Varun Kanade.
*Learning Using Local Membership Queries***(best student paper)** - Ruth Urner, Sharon Wulff and Shai Ben-David.
*PLAL: Cluster-based active learning* - Stanislav Minsker.
*Estimation of Extreme Values and Associated Level Sets of a Regression Function via Selective Sampling* - Maria-Florina Balcan and Phil Long.
*Active and passive learning of linear separators under log-concave distributions*

### Dimensionality reduction and loss functions

Session Chair: Rob Schapire

Long talks (20 minutes + 5 minutes for questions)

- David Woodruff and Qin Zhang.
*Subspace Embeddings and $\ell_p$-Regression Using Exponential Random Variables* - Shivani Agarwal.
*Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper Losses*

Short talk (5 minutes)

- Yining Wang, Liwei Wang, Yuanzhi Li, Di He and Tie-Yan Liu.
*A Theoretical Analysis of NDCG Type Ranking Measures*

### Unsupervised learning

Session Chair: Shai Ben-David

Long talks (20 minutes + 5 minutes for questions)

- Animashree Anandkumar, Rong Ge, Daniel Hsu and Sham Kakade.
*A Tensor Spectral Approach to Learning Mixed Membership Community Models* - Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky and Ananda Theertha Suresh.
*Optimal Probability Estimation with Applications to Prediction and Classification* - Mikhail Belkin, Luis Rademacher and James Voss.
*Blind Signal Separation in the Presence of Gaussian Noise*

Short talks (5 minutes)

- Wouter M. Koolen, Nie Jiazhong and Manfred Warmuth.
*Learning a set of directions* - Marcus Hutter.
*Sparse Adaptive Dirichlet-Like Process Redundancy Bounds*