← Authors

Alkis Kalavasis

20 papers · 2020–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (5) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (28) πŸŒ‰ Interdisciplinary Bridge πŸ‘‘ Triple Crown ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (82) πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (20) ❓ The Questioner (2)

Conferences

NIPS (8) COLT (5) ICML (4) AISTATS (2) ICLR (1)

Top co-authors

Dimitris Fotakis (8) Amin Karbasi (8) Grigoris Velegkas (8) Christos Tzamos (5) Manolis Zampetakis (3) Vasilis Kontonis (3) Steve Hanneke (2) Anay Mehrotra (2) Konstantinos Stavropoulos (2) Felix Zhou (2)

Research topics

Differential Privacy (1)

Keywords

sample complexity (5) differential privacy (3) pac learning (3) algorithmic stability (2) neural network (2) online learning (2) label ranking (2) total variation distance (2) pairwise comparison (2) learning rate (2) model security (1) adversarial machine learning (1) stochastic gradient descent (1) covariance estimation (1) parameter estimation (1) policy gradient (1) learning theory (1) vc dimension (1) statistical query (1) multiclass classification (1)

Papers

Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion ICML 2025
What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness (Extended Abstract) COLT 2025
Universal Rates for Regression: Separations between Cut-Off and Absolute Loss COLT 2024
Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening (Extended Abstract) COLT 2024
Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models NIPS 2024
Replicable Learning of Large-Margin Halfspaces ICML 2024
On the Computational Landscape of Replicable Learning NIPS 2024
Optimal Learners for Realizable Regression: PAC Learning and Online Learning NIPS 2023
Replicable Bandits ICLR 2023
Statistical Indistinguishability of Learning Algorithms ICML 2023
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method NIPS 2023
Linear Label Ranking with Bounded Noise NIPS 2022
Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes NIPS 2022
Learning and Covering Sums of Independent Random Variables with Unbounded Support NIPS 2022
Perfect Sampling from Pairwise Comparisons NIPS 2022
Differentially Private Regression with Unbounded Covariates AISTATS 2022
Label Ranking through Nonparametric Regression ICML 2022
Efficient Algorithms for Learning from Coarse Labels COLT 2021
Aggregating Incomplete and Noisy Rankings AISTATS 2021
Efficient Parameter Estimation of Truncated Boolean Product Distributions COLT 2020