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Editors: Vitaly Feldman, Alexander Rakhlin, Ohad Shamir
Conference on Learning Theory 2016: Preface
; 29th Annual Conference on Learning Theory, PMLR 49:1-3
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Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies
Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar; 29th Annual Conference on Learning Theory, PMLR 49:1639-1642
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Open Problem: Best Arm Identification: Almost Instance-Wise Optimality and the Gap Entropy Conjecture
Lijie Chen, Jian Li; 29th Annual Conference on Learning Theory, PMLR 49:1643-1646
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Open Problem: Kernel methods on manifolds and metric spaces. What is the probability of a positive definite geodesic exponential kernel?
Aasa Feragen, Søren Hauberg; 29th Annual Conference on Learning Theory, PMLR 49:1647-1650
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Open Problem: Second order regret bounds based on scaling time
Yoav Freund; 29th Annual Conference on Learning Theory, PMLR 49:1651-1654
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Open Problem: Property Elicitation and Elicitation Complexity
Rafael Frongillo, Ian Kash, Stephen Becker; 29th Annual Conference on Learning Theory, PMLR 49:1655-1658
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Open Problem: Parameter-Free and Scale-Free Online Algorithms
Francesco Orabona, Dávid Pál; 29th Annual Conference on Learning Theory, PMLR 49:1659-1664
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An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives
Shipra Agrawal, Nikhil R. Devanur, Lihong Li; 29th Annual Conference on Learning Theory, PMLR 49:4-18
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Learning and Testing Junta Distributions
Maryam Aliakbarpour, Eric Blais, Ronitt Rubinfeld; 29th Annual Conference on Learning Theory, PMLR 49:19-46
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Sign rank versus VC dimension
Noga Alon, Shay Moran, Amir Yehudayoff; 29th Annual Conference on Learning Theory, PMLR 49:47-80
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Efficient approaches for escaping higher order saddle points in non-convex optimization
Animashree Anandkumar, Rong Ge; 29th Annual Conference on Learning Theory, PMLR 49:81-102
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Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes
Nima Anari, Shayan Oveis Gharan, Alireza Rezaei; 29th Annual Conference on Learning Theory, PMLR 49:103-115
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An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits
Peter Auer, Chao-Kai Chiang; 29th Annual Conference on Learning Theory, PMLR 49:116-120
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Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models
Bernardo Ávila Pires, Csaba Szepesvári; 29th Annual Conference on Learning Theory, PMLR 49:121-151
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Learning and 1-bit Compressed Sensing under Asymmetric Noise
Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang; 29th Annual Conference on Learning Theory, PMLR 49:152-192
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Reinforcement Learning of POMDPs using Spectral Methods
Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar; 29th Annual Conference on Learning Theory, PMLR 49:193-256
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Highly-Smooth Zero-th Order Online Optimization
Francis Bach, Vianney Perchet; 29th Annual Conference on Learning Theory, PMLR 49:257-283
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An Improved Gap-Dependency Analysis of the Noisy Power Method
Maria-Florina Balcan, Simon Shaolei Du, Yining Wang, Adams Wei Yu; 29th Annual Conference on Learning Theory, PMLR 49:284-309
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Learning Combinatorial Functions from Pairwise Comparisons
Maria-Florina Balcan, Ellen Vitercik, Colin White; 29th Annual Conference on Learning Theory, PMLR 49:310-335
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Instance-dependent Regret Bounds for Dueling Bandits
Akshay Balsubramani, Zohar Karnin, Robert E. Schapire, Masrour Zoghi; 29th Annual Conference on Learning Theory, PMLR 49:336-360
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On the low-rank approach for semidefinite programs arising in synchronization and community detection
Afonso S. Bandeira, Nicolas Boumal, Vladislav Voroninski; 29th Annual Conference on Learning Theory, PMLR 49:361-382
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Information-theoretic thresholds for community detection in sparse networks
Jess Banks, Cristopher Moore, Joe Neeman, Praneeth Netrapalli; 29th Annual Conference on Learning Theory, PMLR 49:383-416
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Noisy Tensor Completion via the Sum-of-Squares Hierarchy
Boaz Barak, Ankur Moitra; 29th Annual Conference on Learning Theory, PMLR 49:417-445
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Basis Learning as an Algorithmic Primitive
Mikhail Belkin, Luis Rademacher, James Voss; 29th Annual Conference on Learning Theory, PMLR 49:446-487
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Aggregation of supports along the Lasso path
Pierre C. Bellec; 29th Annual Conference on Learning Theory, PMLR 49:488-529
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Dropping Convexity for Faster Semi-definite Optimization
Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi; 29th Annual Conference on Learning Theory, PMLR 49:530-582
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Multi-scale exploration of convex functions and bandit convex optimization
Sébastien Bubeck, Ronen Eldan; 29th Annual Conference on Learning Theory, PMLR 49:583-589
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Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem
Alexandra Carpentier, Andrea Locatelli; 29th Annual Conference on Learning Theory, PMLR 49:590-604
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Delay and Cooperation in Nonstochastic Bandits
Nicol‘o Cesa-Bianchi, Claudio Gentile, Yishay Mansour, Alberto Minora; 29th Annual Conference on Learning Theory, PMLR 49:605-622
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On the Approximability of Sparse PCA
Siu On Chan, Dimitris Papailliopoulos, Aviad Rubinstein; 29th Annual Conference on Learning Theory, PMLR 49:623-646
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Pure Exploration of Multi-armed Bandit Under Matroid Constraints
Lijie Chen, Anupam Gupta, Jian Li; 29th Annual Conference on Learning Theory, PMLR 49:647-669
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Provably manipulation-resistant reputation systems
Paul Christiano; 29th Annual Conference on Learning Theory, PMLR 49:670-697
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On the Expressive Power of Deep Learning: A Tensor Analysis
Nadav Cohen, Or Sharir, Amnon Shashua; 29th Annual Conference on Learning Theory, PMLR 49:698-728
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A Light Touch for Heavily Constrained SGD
Andrew Cotter, Maya Gupta, Jan Pfeifer; 29th Annual Conference on Learning Theory, PMLR 49:729-771
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Adaptive Learning with Robust Generalization Guarantees
Rachel Cummings, Katrina Ligett, Kobbi Nissim, Aaron Roth, Zhiwei Steven Wu; 29th Annual Conference on Learning Theory, PMLR 49:772-814
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Complexity Theoretic Limitations on Learning DNF’s
Amit Daniely, Shai Shalev-Shwartz; 29th Annual Conference on Learning Theory, PMLR 49:815-830
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Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables
I. Diakonikolas, D. M. Kane, A. Stewart; 29th Annual Conference on Learning Theory, PMLR 49:831-849
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Properly Learning Poisson Binomial Distributions in Almost Polynomial Time
I. Diakonikolas, D. M. Kane, A. Stewart; 29th Annual Conference on Learning Theory, PMLR 49:850-878
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Asymptotic behavior of \ell_p-based Laplacian regularization in semi-supervised learning
Ahmed El Alaoui, Xiang Cheng, Aaditya Ramdas, Martin J. Wainwright, Michael I. Jordan; 29th Annual Conference on Learning Theory, PMLR 49:879-906
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The Power of Depth for Feedforward Neural Networks
Ronen Eldan, Ohad Shamir; 29th Annual Conference on Learning Theory, PMLR 49:907-940
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Online Learning and Blackwell Approachability in Quitting Games
Janos Flesch, Rida Laraki, Vianney Perchet; 29th Annual Conference on Learning Theory, PMLR 49:941-942
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Spectral thresholds in the bipartite stochastic block model
Laura Florescu, Will Perkins; 29th Annual Conference on Learning Theory, PMLR 49:943-959
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Online Sparse Linear Regression
Dean Foster, Satyen Kale, Howard Karloff; 29th Annual Conference on Learning Theory, PMLR 49:960-970
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Preference-based Teaching
Ziyuan Gao, Christoph Ries, Hans Simon, Sandra Zilles; 29th Annual Conference on Learning Theory, PMLR 49:971-997
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Optimal Best Arm Identification with Fixed Confidence
Aurélien Garivier, Emilie Kaufmann; 29th Annual Conference on Learning Theory, PMLR 49:998-1027
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Maximin Action Identification: A New Bandit Framework for Games
Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen; 29th Annual Conference on Learning Theory, PMLR 49:1028-1050
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Semidefinite Programs for Exact Recovery of a Hidden Community
Bruce Hajek, Yihong Wu, Jiaming Xu; 29th Annual Conference on Learning Theory, PMLR 49:1051-1095
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Online Learning with Low Rank Experts
Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour; 29th Annual Conference on Learning Theory, PMLR 49:1096-1114
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Optimal rates for total variation denoising
Jan-Christian Hütter, Philippe Rigollet; 29th Annual Conference on Learning Theory, PMLR 49:1115-1146
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Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja’s Algorithm
Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford; 29th Annual Conference on Learning Theory, PMLR 49:1147-1164
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Online Isotonic Regression
Wojciech Kotłowski, Wouter M. Koolen, Alan Malek; 29th Annual Conference on Learning Theory, PMLR 49:1165-1189
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Time series prediction and online learning
Vitaly Kuznetsov, Mehryar Mohri; 29th Annual Conference on Learning Theory, PMLR 49:1190-1213
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Regret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits
Tor Lattimore; 29th Annual Conference on Learning Theory, PMLR 49:1214-1245
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Gradient Descent Only Converges to Minimizers
Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht; 29th Annual Conference on Learning Theory, PMLR 49:1246-1257
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Learning Communities in the Presence of Errors
Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan; 29th Annual Conference on Learning Theory, PMLR 49:1258-1291
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On the capacity of information processing systems
Laurent Massoulie, Kuang Xu; 29th Annual Conference on Learning Theory, PMLR 49:1292-1297
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Learning Simple Auctions
Jamie Morgenstern, Tim Roughgarden; 29th Annual Conference on Learning Theory, PMLR 49:1298-1318
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Density Evolution in the Degree-correlated Stochastic Block Model
Elchanan Mossel, Jiaming Xu; 29th Annual Conference on Learning Theory, PMLR 49:1319-1356
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Cortical Computation via Iterative Constructions
Christos Papadimitriou, Samantha Petti, Santosh Vempala; 29th Annual Conference on Learning Theory, PMLR 49:1357-1375
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When can we rank well from comparisons of O(n\log(n)) non-actively chosen pairs?
Arun Rajkumar, Shivani Agarwal; 29th Annual Conference on Learning Theory, PMLR 49:1376-1401
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How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods
Andrej Risteski; 29th Annual Conference on Learning Theory, PMLR 49:1402-1416
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Simple Bayesian Algorithms for Best Arm Identification
Daniel Russo; 29th Annual Conference on Learning Theory, PMLR 49:1417-1418
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Interactive Algorithms: from Pool to Stream
Sivan Sabato, Tom Hess; 29th Annual Conference on Learning Theory, PMLR 49:1419-1439
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Best-of-K-bandits
Max Simchowitz, Kevin Jamieson, Benjamin Recht; 29th Annual Conference on Learning Theory, PMLR 49:1440-1489
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Memory, Communication, and Statistical Queries
Jacob Steinhardt, Gregory Valiant, Stefan Wager; 29th Annual Conference on Learning Theory, PMLR 49:1490-1516
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benefits of depth in neural networks
Matus Telgarsky; 29th Annual Conference on Learning Theory, PMLR 49:1517-1539
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A Guide to Learning Arithmetic Circuits
Ilya Volkovich; 29th Annual Conference on Learning Theory, PMLR 49:1540-1561
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Online learning in repeated auctions
Jonathan Weed, Vianney Perchet, Philippe Rigollet; 29th Annual Conference on Learning Theory, PMLR 49:1562-1583
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The Extended Littlestone’s Dimension for Learning with Mistakes and Abstentions
Chicheng Zhang, Kamalika Chaudhuri; 29th Annual Conference on Learning Theory, PMLR 49:1584-1616
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First-order Methods for Geodesically Convex Optimization
Hongyi Zhang, Suvrit Sra; 29th Annual Conference on Learning Theory, PMLR 49:1617-1638
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