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ORCID29th COLT 2016: New York, USA
- Vitaly Feldman, Alexander Rakhlin, Ohad Shamir:
Proceedings of the 29th Conference on Learning Theory, COLT 2016, New York, USA, June 23-26, 2016. JMLR Workshop and Conference Proceedings 49, JMLR.org 2016
Preface
- Vitaly Feldman, Alexander Rakhlin:
Conference on Learning Theory 2016: Preface. 1-3
Regular Papers
- Shipra Agrawal, Nikhil R. Devanur, Lihong Li:
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives. 4-18 - Maryam Aliakbarpour, Eric Blais, Ronitt Rubinfeld:
Learning and Testing Junta Distributions. 19-46 - Noga Alon, Shay Moran, Amir Yehudayoff:
Sign rank versus VC dimension. 47-80 - Animashree Anandkumar, Rong Ge:
Efficient approaches for escaping higher order saddle points in non-convex optimization. 81-102 - Nima Anari, Shayan Oveis Gharan, Alireza Rezaei:
Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes. 103-115 - Peter Auer, Chao-Kai Chiang:
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits. 116-120 - Bernardo Ávila Pires:
Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models. 121-151 - Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Hongyang Zhang:
Learning and 1-bit Compressed Sensing under Asymmetric Noise. 152-192 - Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar:
Reinforcement Learning of POMDPs using Spectral Methods. 193-256 - Francis R. Bach, Vianney Perchet:
Highly-Smooth Zero-th Order Online Optimization. 257-283 - Maria-Florina Balcan, Simon Shaolei Du, Yining Wang, Adams Wei Yu:
An Improved Gap-Dependency Analysis of the Noisy Power Method. 284-309 - Maria-Florina Balcan, Ellen Vitercik, Colin White:
Learning Combinatorial Functions from Pairwise Comparisons. 310-335 - Akshay Balsubramani, Zohar S. Karnin, Robert E. Schapire, Masrour Zoghi:
Instance-dependent Regret Bounds for Dueling Bandits. 336-360 - Afonso S. Bandeira, Nicolas Boumal, Vladislav Voroninski:
On the low-rank approach for semidefinite programs arising in synchronization and community detection. 361-382 - Jess Banks, Cristopher Moore, Joe Neeman, Praneeth Netrapalli:
Information-theoretic thresholds for community detection in sparse networks. 383-416 - Boaz Barak, Ankur Moitra:
Noisy Tensor Completion via the Sum-of-Squares Hierarchy. 417-445 - Mikhail Belkin, Luis Rademacher
, James R. Voss:
Basis Learning as an Algorithmic Primitive. 446-487 - Pierre C. Bellec:
Aggregation of supports along the Lasso path. 488-529 - Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi:
Dropping Convexity for Faster Semi-definite Optimization. 530-582 - Sébastien Bubeck, Ronen Eldan:
Multi-scale exploration of convex functions and bandit convex optimization. 583-589 - Alexandra Carpentier, Andrea Locatelli:
Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem. 590-604 - Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour, Alberto Minora:
Delay and Cooperation in Nonstochastic Bandits. 605-622 - Siu On Chan, Dimitris Papailliopoulos, Aviad Rubinstein:
On the Approximability of Sparse PCA. 623-646 - Lijie Chen, Anupam Gupta, Jian Li:
Pure Exploration of Multi-armed Bandit Under Matroid Constraints. 647-669 - Paul F. Christiano:
Provably manipulation-resistant reputation systems. 670-697 - Nadav Cohen, Or Sharir, Amnon Shashua:
On the Expressive Power of Deep Learning: A Tensor Analysis. 698-728 - Andrew Cotter, Maya R. Gupta, Jan Pfeifer:
A Light Touch for Heavily Constrained SGD. 729-771 - Rachel Cummings, Katrina Ligett, Kobbi Nissim, Aaron Roth, Zhiwei Steven Wu:
Adaptive Learning with Robust Generalization Guarantees. 772-814 - Amit Daniely, Shai Shalev-Shwartz:
Complexity Theoretic Limitations on Learning DNF's. 815-830 - Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart:
Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables. 831-849 - Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart:
Properly Learning Poisson Binomial Distributions in Almost Polynomial Time. 850-878 - Ahmed El Alaoui:
Asymptotic behavior of \(\ell_p\)-based Laplacian regularization in semi-supervised learning. 879-906 - Ronen Eldan, Ohad Shamir:
The Power of Depth for Feedforward Neural Networks. 907-940 - János Flesch, Rida Laraki, Vianney Perchet:
Online Learning and Blackwell Approachability in Quitting Games. 941-942 - Laura Florescu, Will Perkins:
Spectral thresholds in the bipartite stochastic block model. 943-959 - Dean P. Foster, Satyen Kale, Howard J. Karloff:
Online Sparse Linear Regression. 960-970 - Ziyuan Gao, Christoph Ries, Hans Ulrich Simon, Sandra Zilles:
Preference-based Teaching. 971-997 - Aurélien Garivier, Emilie Kaufmann:
Optimal Best Arm Identification with Fixed Confidence. 998-1027 - Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen:
Maximin Action Identification: A New Bandit Framework for Games. 1028-1050 - Bruce E. Hajek, Yihong Wu, Jiaming Xu:
Semidefinite Programs for Exact Recovery of a Hidden Community. 1051-1095 - Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour:
Online Learning with Low Rank Experts. 1096-1114 - Jan-Christian Hü:
Optimal rates for total variation denoising. 1115-1146 - Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford:
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm. 1147-1164 - Wojciech Kotlowski:
Online Isotonic Regression. 1165-1189 - Vitaly Kuznetsov, Mehryar Mohri:
Time series prediction and online learning. 1190-1213 - Tor Lattimore:
Regret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits. 1214-1245 - Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht:
Gradient Descent Only Converges to Minimizers. 1246-1257 - Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan:
Learning Communities in the Presence of Errors. 1258-1291 - Laurent Massoulié, Kuang Xu:
On the capacity of information processing systems. 1292-1297 - Jamie Morgenstern, Tim Roughgarden:
Learning Simple Auctions. 1298-1318 - Elchanan Mossel, Jiaming Xu:
Density Evolution in the Degree-correlated Stochastic Block Model. 1319-1356 - Christos H. Papadimitriou, Samantha Petti, Santosh S. Vempala:
Cortical Computation via Iterative Constructions. 1357-1375 - Arun Rajkumar, Shivani Agarwal:
When can we rank well from comparisons of \(O(n\log(n))\) non-actively chosen pairs? 1376-1401 - Andrej Risteski:
How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods. 1402-1416 - Daniel Russo:
Simple Bayesian Algorithms for Best Arm Identification. 1417-1418 - Sivan Sabato, Tom Hess:
Interactive Algorithms: from Pool to Stream. 1419-1439 - Max Simchowitz, Kevin G. Jamieson, Benjamin Recht:
Best-of-K-bandits. 1440-1489 - Jacob Steinhardt, Gregory Valiant, Stefan Wager:
Memory, Communication, and Statistical Queries. 1490-1516 - Matus Telgarsky:
benefits of depth in neural networks. 1517-1539 - Ilya Volkovich:
A Guide to Learning Arithmetic Circuits. 1540-1561 - Jonathan Weed, Vianney Perchet, Philippe Rigollet:
Online learning in repeated auctions. 1562-1583 - Chicheng Zhang, Kamalika Chaudhuri:
The Extended Littlestone's Dimension for Learning with Mistakes and Abstentions. 1584-1616 - Hongyi Zhang, Suvrit Sra:
First-order Methods for Geodesically Convex Optimization. 1617-1638
Open Problems
- Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar:
Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. 1639-1642 - Lijie Chen, Jian Li:
Open Problem: Best Arm Identification: Almost Instance-Wise Optimality and the Gap Entropy Conjecture. 1643-1646 - Aasa Feragen, Søren Hauberg:
Open Problem: Kernel methods on manifolds and metric spaces. What is the probability of a positive definite geodesic exponential kernel? 1647-1650 - Yoav Freund:
Open Problem: Second order regret bounds based on scaling time. 1651-1654 - Rafael M. Frongillo, Ian A. Kash, Stephen Becker:
Open Problem: Property Elicitation and Elicitation Complexity. 1655-1658 - Francesco Orabona, Dávid Pál:
Open Problem: Parameter-Free and Scale-Free Online Algorithms. 1659-1664
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