Jayakrishnan Nair

1. Bandit algorithms: Letting go of logarithmic regret for statistical robustness
   2020/06/22 by Kumar Ashutosh, Ashutosh, Kumar, Jayakrishnan Nair +5 · 3 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Reinforcement Learning in Robotics #Stochastic Gradient Optimization Techniques
2. Constrained Pure Exploration Multi-Armed Bandits with a Fixed Budget
   2022/11/27 by Fathima Zarin Faizal, Jayakrishnan Nair, Faizal, Fathima Zarin +1 · 3 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
3. Constrained regret minimization for multi-criterion multi-armed bandits
   2020/06/17 by Anmol Kagrecha, Kagrecha, Anmol, Jayakrishnan Nair +3 · 2 citations
   Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Energy Load and Power Forecasting #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Risk and Portfolio Optimization
4. Sizing Storage for Reliable Renewable Integration: A Large Deviations\n Approach
   2019/04/09 by Vivek Deulkar, Jayakrishnan Nair, Deulkar, Vivek +3 · 1 citation
   Engineering · Environmental Science · #Electric Vehicles and Infrastructure #Energy and Environment Impacts #Smart Grid Energy Management
5. Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
   2019/06/03 by Anmol Kagrecha, Kagrecha, Anmol, Jayakrishnan Nair +3 · 1 citation
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Search Problems