![](https://dblp.dagstuhl.de/img/logo.ua.320x120.png)
![](https://dblp.dagstuhl.de/img/dropdown.dark.16x16.png)
![](https://dblp.dagstuhl.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.dagstuhl.de/img/search.dark.16x16.png)
![search dblp](https://dblp.dagstuhl.de/img/search.dark.16x16.png)
default search action
27. ALT 2016: Bari, Italy
- Ronald Ortner, Hans Ulrich Simon
, Sandra Zilles:
Algorithmic Learning Theory - 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings. Lecture Notes in Computer Science 9925, 2016, ISBN 978-3-319-46378-0
Error Bounds, Sample Compression Schemes
- Andreas Maurer:
A Vector-Contraction Inequality for Rademacher Complexities. 3-17 - Nikita Zhivotovskiy, Steve Hanneke:
Localization of VC Classes: Beyond Local Rademacher Complexities. 18-33 - Shay Moran, Manfred K. Warmuth:
Labeled Compression Schemes for Extremal Classes. 34-49 - Shai Ben-David, Ruth Urner:
On Version Space Compression. 50-64
Statistical Learning Theory, Evolvability
- Corinna Cortes, Giulia DeSalvo, Mehryar Mohri:
Learning with Rejection. 67-82 - Lijun Zhang, Tianbao Yang, Rong Jin, Zhi-Hua Zhou:
Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach. 83-97 - Dimitrios I. Diochnos
:
On the Evolution of Monotone Conjunctions: Drilling for Best Approximations. 98-112
Exact and Interactive Learning, Complexity of Teaching Models
- Nader H. Bshouty, Areej Costa:
Exact Learning of Juntas from Membership Queries. 115-129 - Sivan Sabato
:
Submodular Learning and Covering with Response-Dependent Costs. 130-144 - Achilles Beros, Ziyuan Gao, Sandra Zilles:
Classifying the Arithmetical Complexity of Teaching Models. 145-160
Inductive Inference
- Klaus Ambos-Spies:
Learning Finite Variants of Single Languages from Informant. 163-173 - Sanjay Jain, Efim B. Kinber:
Intrinsic Complexity of Partial Learning. 174-188 - Rupert Hölzl, Sanjay Jain, Frank Stephan
:
Learning Pattern Languages over Groups. 189-203
Online Learning
- Nader H. Bshouty, Catherine A. Haddad-Zaknoon:
The Maximum Cosine Framework for Deriving Perceptron Based Linear Classifiers. 207-222 - Mehryar Mohri, Scott Yang:
Structural Online Learning. 223-237 - Yuri Kalnishkan
:
An Upper Bound for Aggregating Algorithm for Regression with Changing Dependencies. 238-252 - Daniil Ryabko:
Things Bayes Can't Do. 253-260 - Wojciech Kotlowski:
On Minimaxity of Follow the Leader Strategy in the Stochastic Setting. 261-275 - Takumi Nakazono, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto:
A Combinatorial Metrical Task System Problem Under the Uniform Metric. 276-287 - Tugkan Batu
, Pongphat Taptagaporn:
Competitive Portfolio Selection Using Stochastic Predictions. 288-302
Bandits and Reinforcement Learning
- Anna Harutyunyan, Marc G. Bellemare, Tom Stepleton, Rémi Munos:
Q(λ) with Off-Policy Corrections. 305-320 - Che-Yu Liu, Lihong Li:
On the Prior Sensitivity of Thompson Sampling. 321-336
Clustering
- Shrinu Kushagra, Samira Samadi, Shai Ben-David:
Finding Meaningful Cluster Structure Amidst Background Noise. 339-354 - Emilie Kaufmann, Thomas Bonald, Marc Lelarge:
A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks. 355-370
![](https://dblp.dagstuhl.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.