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Alkis Kalavasis
Tytuł
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Statistical indistinguishability of learning algorithms
A Kalavasis, A Karbasi, S Moran, G Velegkas
International Conference on Machine Learning 40, 2023
192023
Efficient algorithms for learning from coarse labels
D Fotakis, A Kalavasis, V Kontonis, C Tzamos
Conference on Learning Theory, 2060-2079, 2021
182021
Efficient parameter estimation of truncated boolean product distributions
D Fotakis, A Kalavasis, C Tzamos
Conference on learning theory, 1586-1600, 2020
182020
Replicable bandits
H Esfandiari, A Kalavasis, A Karbasi, A Krause, V Mirrokni, G Velegkas
arXiv preprint arXiv:2210.01898, 2022
172022
Optimal Learners for Realizable Regression: PAC Learning and Online Learning
I Attias, S Hanneke, A Kalavasis, A Karbasi, G Velegkas
Advances in Neural Information Processing Systems 36, 2023
112023
Differentially private regression with unbounded covariates
J Milionis, A Kalavasis, D Fotakis, S Ioannidis
International Conference on Artificial Intelligence and Statistics, 3242-3273, 2022
112022
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes
A Kalavasis, G Velegkas, A Karbasi
Advances in Neural Information Processing Systems 35, 2022
92022
Aggregating incomplete and noisy rankings
D Fotakis, A Kalavasis, K Stavropoulos
International conference on artificial intelligence and statistics, 2278-2286, 2021
82021
Label ranking through nonparametric regression
D Fotakis, A Kalavasis, E Psaroudaki
International Conference on Machine Learning, 6622-6659, 2022
72022
Linear label ranking with bounded noise
D Fotakis, A Kalavasis, V Kontonis, C Tzamos
Advances in Neural Information Processing Systems 35, 15642-15656, 2022
42022
Perfect Sampling from Pairwise Comparisons
D Fotakis, A Kalavasis, C Tzamos
Advances in Neural Information Processing Systems 35, 2022
42022
Replicable learning of large-margin halfspaces
A Kalavasis, A Karbasi, KG Larsen, G Velegkas, F Zhou
arXiv preprint arXiv:2402.13857, 2024
32024
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods
C Caramanis, D Fotakis, A Kalavasis, V Kontonis, C Tzamos
Advances in Neural Information Processing Systems 36, 2023
32023
Transfer learning beyond bounded density ratios
A Kalavasis, I Zadik, M Zampetakis
arXiv preprint arXiv:2403.11963, 2024
22024
Learning and covering sums of independent random variables with unbounded support
A Kalavasis, K Stavropoulos, E Zampetakis
Advances in Neural Information Processing Systems 35, 25185-25197, 2022
22022
On the Computational Landscape of Replicable Learning
A Kalavasis, A Karbasi, G Velegkas, F Zhou
arXiv preprint arXiv:2405.15599, 2024
12024
Learning Hard-Constrained Models with One Sample
A Galanis, A Kalavasis, AV Kandiros
Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024
12024
On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games
I Anagnostides, A Kalavasis, T Sandholm, M Zampetakis
arXiv preprint arXiv:2311.14869, 2023
12023
On Sampling from Ising Models with Spectral Constraints
A Galanis, A Kalavasis, AV Kandiros
arXiv preprint arXiv:2407.07645, 2024
2024
Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening
A Kalavasis, A Mehrotra, M Zampetakis
The Thirty Seventh Annual Conference on Learning Theory, 2767-2767, 2024
2024
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