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28. ALT 2017: Kyoto, Japan
- Steve Hanneke, Lev Reyzin:
International Conference on Algorithmic Learning Theory, ALT 2017, 15-17 October 2017, Kyoto University, Kyoto, Japan. Proceedings of Machine Learning Research 76, PMLR 2017 - Algorithmic Learning Theory (ALT) 2017: Preface. 1-2
- Philip M. Long:
New bounds on the price of bandit feedback for mistake-bounded online multiclass learning. 3-10 - Henry W. J. Reeve, Gavin Brown:
Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours. 11-56 - Daniil Ryabko:
Universality of Bayesian mixture predictors. 57-71 - Fahimeh Bayeh, Ziyuan Gao, Sandra Zilles:
Erasing Pattern Languages Distinguishable by a Finite Number of Strings. 72-108 - Nader H. Bshouty, Nuha Diab, Shada R. Kawar, Robert J. Shahla:
Non-Adaptive Randomized Algorithm for Group Testing. 109-128 - Rupert Hölzl, Sanjay Jain, Philipp Schlicht, Karen Seidel, Frank Stephan:
Automatic Learning from Repetitive Texts. 129-150 - Odalric-Ambrym Maillard:
Boundary Crossing for General Exponential Families. 151-184 - Ziyuan Gao, David G. Kirkpatrick, Christoph Ries, Hans Ulrich Simon, Sandra Zilles:
Preference-based Teaching of Unions of Geometric Objects. 185-207 - Vadim V. Lozin, Igor Razgon, Viktor Zamaraev, Elena Zamaraeva, Nikolai Yu. Zolotykh:
Specifying a positive threshold function via extremal points. 208-222 - Pierre Ménard, Aurélien Garivier:
A minimax and asymptotically optimal algorithm for stochastic bandits. 223-237 - Mano Vikash Janardhanan:
Graph Verification with a Betweenness Oracle. 238-249 - Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan:
Lifelong Learning in Costly Feature Spaces. 250-287 - Jungseul Ok, Se-Young Yun, Alexandre Proutière, Rami Mochaourab:
Collaborative Clustering: Sample Complexity and Efficient Algorithms. 288-329 - Arushi Gupta, Daniel Hsu:
Parameter identification in Markov chain choice models. 330-340 - Danielle Ensign, Scott Neville, Arnab Paul, Suresh Venkatasubramanian:
The Complexity of Explaining Neural Networks Through (group) Invariants. 341-359 - Hayato Mizumoto, Shota Todoroki, Diptarama, Ryo Yoshinaka, Ayumi Shinohara:
An efficient query learning algorithm for zero-suppressed binary decision diagrams. 360-371 - Laurent Orseau, Tor Lattimore, Shane Legg:
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss. 372-399 - Daniil Ryabko:
Hypotheses testing on infinite random graphs. 400-411 - Wojciech Kotlowski:
Scale-Invariant Unconstrained Online Learning. 412-433 - Martin Grohe, Christof Löding, Martin Ritzert:
Learning MSO-definable hypotheses on strings. 434-451 - Dana Angluin, Tyler Dohrn:
The Power of Random Counterexamples. 452-465 - Niklas Thiemann, Christian Igel, Olivier Wintenberger, Yevgeny Seldin:
A Strongly Quasiconvex PAC-Bayesian Bound. 466-492 - Timo Kötzing, Martin Schirneck, Karen Seidel:
Normal Forms in Semantic Language Identification. 493-516 - Jaouad Mourtada
, Odalric-Ambrym Maillard:
Efficient tracking of a growing number of experts. 517-539 - Vitaly Feldman, Pravesh Kothari, Jan Vondrák:
Tight Bounds on ℓ1 Approximation and Learning of Self-Bounding Functions. 540-559 - Di Chen, Jeff M. Phillips:
Relative Error Embeddings of the Gaussian Kernel Distance. 560-576 - Alan Fern, Robby Goetschalckx, Mandana Hamidi-Haines, Prasad Tadepalli
:
Adaptive Submodularity with Varying Query Sets: An Application to Active Multi-label Learning. 577-592 - Ruitong Huang, Mohammad M. Ajallooeian, Csaba Szepesvári, Martin Müller:
Structured Best Arm Identification with Fixed Confidence. 593-616 - Ata Kabán:
On Compressive Ensemble Induced Regularisation: How Close is the Finite Ensemble Precision Matrix to the Infinite Ensemble? 617-628 - Vitaly Feldman:
Dealing with Range Anxiety in Mean Estimation via Statistical Queries. 629-640 - Yuyi Wang, Zheng-Chu Guo, Jan Ramon:
Learning from Networked Examples. 641-666 - Ning Ding, Yanli Ren, Dawu Gu:
PAC Learning Depth-3 $\textrm{AC}^0$ Circuits of Bounded Top Fanin. 667-680 - Pooria Joulani, András György, Csaba Szepesvári:
A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds. 681-720
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