Anmol Kagrecha

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 11

Top Topics

Regret Minimization

Service Systems

Multi Armed Bandits

Top Venues

IEEE Trans. Inf. Theory

Publications

Anmol Kagrecha, Henrik Marklund, Benjamin Van Roy, Hong Jun Jeon, Richard Zeckhauser
Adaptive Crowdsourcing Via Self-Supervised Learning. CoRR (2024)
Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
Constrained regret minimization for multi-criterion multi-armed bandits. Mach. Learn. 112 (2) (2023)
Anmol Kagrecha, Jayakrishnan Nair, Krishna P. Jagannathan
Statistically Robust, Risk-Averse Best Arm Identification in Multi-Armed Bandits. IEEE Trans. Inf. Theory 68 (8) (2022)
Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna P. Jagannathan
Bandit algorithms: Letting go of logarithmic regret for statistical robustness. AISTATS (2021)
Anmol Kagrecha, Jayakrishnan Nair, Krishna P. Jagannathan
Statistically Robust, Risk-Averse Best Arm Identification in Multi-Armed Bandits. CoRR (2020)
Anmol Kagrecha, Jayakrishnan Nair, Krishna P. Jagannathan
Constrained regret minimization for multi-criterion multi-armed bandits. CoRR (2020)
Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna P. Jagannathan
Bandit algorithms: Letting go of logarithmic regret for statistical robustness. CoRR (2020)
Anmol Kagrecha, Jayakrishnan Nair
"Please Come Back Later": Benefiting from Deferrals in Service Systems. COMSNETS (2020)
Anmol Kagrecha, Jayakrishnan Nair
Please come back later: Benefiting from deferrals in service systems. CoRR (2019)
Anmol Kagrecha, Jayakrishnan Nair, Krishna P. Jagannathan
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards. NeurIPS (2019)
Anmol Kagrecha, Jayakrishnan Nair, Krishna P. Jagannathan
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards. CoRR (2019)