Alkis Kalavasis

According to our database, Alkis Kalavasis authored at least 27 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Computational Lower Bounds for Regret Minimization in Normal-Form Games.

Ioannis Anagnostides, Alkis Kalavasis, Tuomas Sandholm

CoRR, 2024

Barriers to Welfare Maximization with No-Regret Learning.

Ioannis Anagnostides, Alkis Kalavasis, Tuomas Sandholm

CoRR, 2024

Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening.

Alkis Kalavasis, Anay Mehrotra, Manolis Zampetakis

CoRR, 2024

Injecting Undetectable Backdoors in Deep Learning and Language Models.

Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis

CoRR, 2024

On the Computational Landscape of Replicable Learning.

Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou

CoRR, 2024

Transfer Learning Beyond Bounded Density Ratios.

Alkis Kalavasis, Ilias Zadik, Manolis Zampetakis

CoRR, 2024

Learning Hard-Constrained Models with One Sample.

Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros

Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games.

Ioannis Anagnostides, Alkis Kalavasis, Tuomas Sandholm, Manolis Zampetakis

Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

Replicable Learning of Large-Margin Halfspaces.

Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening (Extended Abstract).

Alkis Kalavasis, Anay Mehrotra, Manolis Zampetakis

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Universal Rates for Regression: Separations between Cut-Off and Absolute Loss.

Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

On Sampling from Ising Models with Spectral Constraints.

Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros

Proceedings of the Approximation, 2024

2023

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods.

Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos

CoRR, 2023

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method.

Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimal Learners for Realizable Regression: PAC Learning and Online Learning.

Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Statistical Indistinguishability of Learning Algorithms.

Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas

Proceedings of the International Conference on Machine Learning, 2023

Replicable Bandits.

Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Reproducible Bandits.

Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas

CoRR, 2022

Efficient Parameter Estimation of Truncated Boolean Product Distributions.

Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos

Algorithmica, 2022

Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes.

Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning and Covering Sums of Independent Random Variables with Unbounded Support.

Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Perfect Sampling from Pairwise Comparisons.

Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Linear Label Ranking with Bounded Noise.

Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Label Ranking through Nonparametric Regression.

Dimitris Fotakis, Alkis Kalavasis, Eleni Psaroudaki

Proceedings of the International Conference on Machine Learning, 2022

Differentially Private Regression with Unbounded Covariates.

Jason Milionis, Alkis Kalavasis, Dimitris A. Fotakis, Stratis Ioannidis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Efficient Algorithms for Learning from Coarse Labels.

Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos

Proceedings of the Conference on Learning Theory, 2021

Aggregating Incomplete and Noisy Rankings.

Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021