Alkis Kalavasis

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 37

Top Topics

Gradient Method

Pairwise Comparison

Top Venues

Publications

Ioannis Anagnostides, Alkis Kalavasis, Tuomas Sandholm, Manolis Zampetakis
On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games. ITCS (2024)
Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas, Felix Zhou
On the Computational Landscape of Replicable Learning. CoRR (2024)
Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis
Injecting Undetectable Backdoors in Deep Learning and Language Models. CoRR (2024)
Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros
On Sampling from Ising Models with Spectral Constraints. CoRR (2024)
Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros
Learning Hard-Constrained Models with One Sample. SODA (2024)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss. COLT (2024)
Alkis Kalavasis, Anay Mehrotra, Manolis Zampetakis
Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening (Extended Abstract). COLT (2024)
Alkis Kalavasis, Amin Karbasi, Kasper Green Larsen, Grigoris Velegkas, Felix Zhou
Replicable Learning of Large-Margin Halfspaces. CoRR (2024)
Alkis Kalavasis, Ilias Zadik, Manolis Zampetakis
Transfer Learning Beyond Bounded Density Ratios. CoRR (2024)
Ioannis Anagnostides, Alkis Kalavasis, Tuomas Sandholm, Manolis Zampetakis
On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games. CoRR (2023)
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Statistical Indistinguishability of Learning Algorithms. CoRR (2023)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. NeurIPS (2023)
Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods. CoRR (2023)
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Statistical Indistinguishability of Learning Algorithms. ICML (2023)
Andreas Galanis, Alkis Kalavasis, Anthimos Vardis Kandiros
Learning Hard-Constrained Models with One Sample. CoRR (2023)
Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method. NeurIPS (2023)
Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
Replicable Bandits. ICLR (2023)
Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas
Optimal Learners for Realizable Regression: PAC Learning and Online Learning. CoRR (2023)
Jason Milionis, Alkis Kalavasis, Dimitris A. Fotakis, Stratis Ioannidis
Differentially Private Regression with Unbounded Covariates. AISTATS (2022)
Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos
Perfect Sampling from Pairwise Comparisons. NeurIPS (2022)
Alkis Kalavasis, Konstantinos Stavropoulos, Manolis Zampetakis
Learning and Covering Sums of Independent Random Variables with Unbounded Support. CoRR (2022)
Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas
Reproducible Bandits. CoRR (2022)
Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Linear Label Ranking with Bounded Noise. NeurIPS (2022)
Dimitris Fotakis, Alkis Kalavasis, Eleni Psaroudaki
Label Ranking through Nonparametric Regression. ICML (2022)
Jason Milionis, Alkis Kalavasis, Dimitris Fotakis, Stratis Ioannidis
Differentially Private Regression with Unbounded Covariates. CoRR (2022)
Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. CoRR (2022)
Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. NeurIPS (2022)
Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos
Perfect Sampling from Pairwise Comparisons. CoRR (2022)
Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis
Learning and Covering Sums of Independent Random Variables with Unbounded Support. NeurIPS (2022)
Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos
Efficient Parameter Estimation of Truncated Boolean Product Distributions. Algorithmica 84 (8) (2022)
Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos
Aggregating Incomplete and Noisy Rankings. AISTATS (2021)
Dimitris Fotakis, Alkis Kalavasis, Eleni Psaroudaki
Label Ranking through Nonparametric Regression. CoRR (2021)
Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Efficient Algorithms for Learning from Coarse Labels. CoRR (2021)
Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos
Efficient Algorithms for Learning from Coarse Labels. COLT (2021)
Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos
Efficient Parameter Estimation of Truncated Boolean Product Distributions. COLT (2020)
Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos
Efficient Parameter Estimation of Truncated Boolean Product Distributions. CoRR (2020)
Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos
Aggregating Incomplete and Noisy Rankings. CoRR (2020)