Akshay Krishnamurthy
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 10%
- Computational Mechanics top 10%
- Co-authors
- Aarti SinghKirthevasan KandasamyJohn LangfordAlekh AgarwalBarnabás PóczosAndrew McCallumJeff SchneiderLarry Wasserman
- Topics
- Advanced Bandit Algorithms Research (18 papers)Machine Learning and Algorithms (16 papers)Reinforcement Learning in Robotics (7 papers)
- Journals
- Operations ResearchJournal of Machine Learning ResearcharXiv (Cornell University)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Akshay Krishnamurthy
36 papers receiving 441 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 293
- Computer Networks and Communications 89
- Computer Vision and Pattern Recognition 83
- Management Science and Operations Research 73
- Computational Mechanics 70
Countries citing papers authored by Akshay Krishnamurthy
This map shows the geographic impact of Akshay Krishnamurthy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Akshay Krishnamurthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akshay Krishnamurthy more than expected).
Fields of papers citing papers by Akshay Krishnamurthy
This network shows the impact of papers produced by Akshay Krishnamurthy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Akshay Krishnamurthy. The network helps show where Akshay Krishnamurthy may publish in the future.
Co-authorship network of co-authors of Akshay Krishnamurthy
This figure shows the co-authorship network connecting the top 25 collaborators of Akshay Krishnamurthy. A scholar is included among the top collaborators of Akshay Krishnamurthy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Akshay Krishnamurthy. Akshay Krishnamurthy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Optimism in Reinforcement Learning with Generalized Linear Function Approximation | 2 |
| 2 | Bayesian decision-making under misspecified priors with applications to meta-learning | 1 |
| 3 | Provably adaptive reinforcement learning in metric spaces | 1 |
| 4 | Open Problem: Model Selection for Contextual Bandits | 1 |
| 5 | Doubly robust off-policy evaluation with shrinkage | 2 |
| 6 | Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds | 22 |
| 7 | Information Theoretic Regret Bounds for Online Nonlinear Control. | 1 |
| 8 | Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning | 6 |
| 9 | Corrupted Multidimensional Binary Search: Learning in the Presence of Irrational Agents | 0 |
| 10 | Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments. | 5 |
| 11 | Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches | 9 |
| 12 | Model Selection for Contextual Bandits | 1 |
| 13 | Sample Complexity of Learning Mixture of Sparse Linear Regressions | 2 |
| 14 | Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting | 1 |
| 15 | Parallelised Bayesian Optimisation via Thompson Sampling | 44 |
| 16 | Go for a Walk and Arrive at the Answer: Reasoning Over Knowledge Bases with Reinforcement Learning. | 4 |
| 17 | Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning. | 20 |
| 18 | Active Learning for Cost-Sensitive Classification | 4 |
| 19 | Open Problem: First-Order Regret Bounds for Contextual Bandits | 0 |
| 20 | An online hierarchical algorithm for extreme clustering | 2 |
About Akshay Krishnamurthy
Akshay Krishnamurthy is a scholar working on Computational Mathematics, Management Science and Operations Research and Artificial Intelligence, having authored 40 papers that have together received 457 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (18 papers), Machine Learning and Algorithms (16 papers) and Reinforcement Learning in Robotics (7 papers). The work is most often cited by research in Computational Mathematics (24 citations), Artificial Intelligence (293 citations) and Management Science and Operations Research (73 citations). Akshay Krishnamurthy has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Aarti Singh, Kirthevasan Kandasamy, John Langford, Alekh Agarwal, Barnabás Póczos, Andrew McCallum, Jeff Schneider, Larry Wasserman, Hal Daumé and James Sharpnack. Their work appears in journals such as Operations Research, Journal of Machine Learning Research and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.