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