ALT 2017

34 papers

A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds

Pooria Joulani, András György, Csaba Szepesvári

PAC Learning Depth-3 AC^0 Circuits of Bounded Top Fanin

Ning Ding, Yanli Ren, Dawu Gu

Learning from Networked Examples

Yuyi Wang, Zheng-Chu Guo, Jan Ramon

Dealing with Range Anxiety in Mean Estimation via Statistical Queries

Vitaly Feldman

On Compressive Ensemble Induced Regularisation: How Close is the Finite Ensemble Precision Matrix to the Infinite Ensemble?

Ata Kaban

Structured Best Arm Identification with Fixed Confidence

Ruitong Huang, Mohammad M. Ajallooeian, Csaba Szepesvári, Martin Müller

Adaptive Submodularity with Varying Query Sets: An Application to Active Multi-label Learning

Alan Fern, Robby Goetschalckx, Mandana Hamidi-Haines, Prasad Tadepalli

Relative Error Embeddings of the Gaussian Kernel Distance

Di Chen, Jeff M. Phillips

Tight Bounds on ℓ_1 Approximation and Learning of Self-Bounding Functions

Vitaly Feldman, Pravesh Kothari, Jan Vondrak

Efficient tracking of a growing number of experts

Jaouad Mourtada, Odalric-ambrym Maillard

Normal Forms in Semantic Language Identification

Timo Kötzing, Martin Schirneck, Karen Seidel

A Strongly Quasiconvex PAC-Bayesian Bound

Niklas Thiemann, Christian Igel, Olivier Wintenberger, Yevgeny Seldin

The Power of Random Counterexamples

Dana Angluin, Tyler Dohrn

Learning MSO-definable hypotheses on strings

Martin Grohe, Christof Löding, Martin Ritzert

Scale-Invariant Unconstrained Online Learning

Wojciech Kotłowski

Hypotheses testing on infinite random graphs

Daniil Ryabko

Soft-Bayes: Prod for Mixtures of Experts with Log-Loss

Laurent Orseau, Tor Lattimore, Shane Legg

An efficient query learning algorithm for zero-suppressed binary decision diagrams

Hayato Mizumoto, Shota Todoroki, Diptarama, Ryo Yoshinaka, Ayumi Shinohara

The Complexity of Explaining Neural Networks Through (group) Invariants

Danielle Ensign, Scott Neville, Arnab Paul, Suresh Venkatasubramanian

Parameter identification in Markov chain choice models

Arushi Gupta, Daniel Hsu

Collaborative Clustering: Sample Complexity and Efficient Algorithms

Jungseul Ok, Se-Young Yun, Alexandre Proutiere, Rami Mochaourab

Lifelong Learning in Costly Feature Spaces

Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan

Graph Verification with a Betweenness Oracle

Mano Vikash Janardhanan

A minimax and asymptotically optimal algorithm for stochastic bandits

Pierre Menard, Aurélien Garivier

Specifying a positive threshold function via extremal points

Vadim Lozin, Igor Razgon, Viktor Zamaraev, Elena Zamaraeva, Nikolai Yu. Zolotykh

Preference-based Teaching of Unions of Geometric Objects

Ziyuan Gao, David Kirkpatrick, Christoph Ries, Hans Simon, Sandra Zilles

Boundary Crossing for General Exponential Families

Odalric-ambrym Maillard

Automatic Learning from Repetitive Texts

Rupert Hölzl, Sanjay Jain, Philipp Schlicht, Karen Seidel, Frank Stephan

Non-Adaptive Randomized Algorithm for Group Testing

Nader H. Bshouty, Nuha Diab, Shada R. Kawar, Robert J. Shahla

Erasing Pattern Languages Distinguishable by a Finite Number of Strings

Fahimeh Bayeh, Ziyuan Gao, Sandra Zilles

Universality of Bayesian mixture predictors

Daniil Ryabko

Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours

Henry W. J. Reeve, Gavin Brown

New bounds on the price of bandit feedback for mistake-bounded online multiclass learning

Philip M. Long

Algorithmic Learning Theory (ALT) 2017: Preface

Steve Hanneke, Lev Reyzin