Akshat Kumar
Singapore Management University
H-index: 24
Asia-Singapore
Top articles of Akshat Kumar
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Unified training of universal time series forecasting transformers | arXiv preprint arXiv:2402.02592 | Gerald Woo Chenghao Liu Akshat Kumar Caiming Xiong Silvio Savarese | 2024/2/4 |
Difference of Convex Functions Programming for Policy Optimization in Reinforcement Learning | Akshat Kumar | 2024/5/6 | |
Factored MDP based Moving Target Defense with Dynamic Threat Modeling | Megha Bose Praveen Paruchuri Akshat Kumar | 2024/5/6 | |
Leveraging AI Planning For Detecting Cloud Security Vulnerabilities | arXiv preprint arXiv:2402.10985 | Mikhail Kazdagli Mohit Tiwari Akshat Kumar | 2024/2/16 |
FlowPG: Action-constrained Policy Gradient with Normalizing Flows | Advances in Neural Information Processing Systems | Janaka Brahmanage Jiajing Ling Akshat Kumar | 2024/2/13 |
Planning and learning for non-markovian negative side effects using finite state controllers | Proceedings of the AAAI Conference on Artificial Intelligence | Aishwarya Srivastava Sandhya Saisubramanian Praveen Paruchuri Akshat Kumar Shlomo Zilberstein | 2023/6/26 |
Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming | Proceedings of the AAAI Conference on Artificial Intelligence | Aravinth Chembu Scott Sanner Hassan Khurram Akshat Kumar | 2023/6/26 |
Mean-field games among teams | arXiv preprint arXiv:2310.12282 | Jayakumar Subramanian Akshat Kumar Aditya Mahajan | 2023/10/18 |
A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination | Jihwan Jeong Scott Sanner Akshat Kumar | 2023/5/23 | |
Pushing the limits of pre-training for time series forecasting in the cloudops domain | arXiv preprint arXiv:2310.05063 | Gerald Woo Chenghao Liu Akshat Kumar Doyen Sahoo | 2023/10/8 |
Knowledge compilation for constrained combinatorial action spaces in reinforcement learning | Jiajing Ling Moritz Lukas Schuler Akshat Kumar Pradeep Varakantham | 2023 | |
Learning deep time-index models for time series forecasting | Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar Steven Hoi | 2023/7/3 | |
Safe MDP planning by learning temporal patterns of undesirable trajectories and averting negative side effects | Proceedings of the International Conference on Automated Planning and Scheduling | Siow Meng Low Akshat Kumar Scott Sanner | 2023/7/1 |
Constrained multiagent reinforcement learning for large agent population | Jiajing Ling Arambam James Singh Nguyen Duc Thien Akshat Kumar | 2022/8 | |
Trajectory optimization for safe navigation in maritime traffic using historical data | Chaithanya Basrur Arambam James Singh Arunesh Sinha Akshat Kumar TK Kumar | 2022 | |
Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs | Proceedings of the AAAI Conference on Artificial Intelligence | Siow Meng Low Akshat Kumar Scott Sanner | 2022/6/28 |
Using constraint programming and graph representation learning for generating interpretable cloud security policies | arXiv preprint arXiv:2205.01240 | Mikhail Kazdagli Mohit Tiwari Akshat Kumar | 2022/5/2 |
Cost: Contrastive learning of disentangled seasonal-trend representations for time series forecasting | arXiv preprint arXiv:2202.01575 | Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar Steven Hoi | 2022/2/3 |
Deeptime: Deep time-index meta-learning for non-stationary time-series forecasting | Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar Steven Hoi | 2022/9/29 | |
Etsformer: Exponential smoothing transformers for time-series forecasting | arXiv preprint arXiv:2202.01381 | Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar Steven Hoi | 2022/2/3 |
Co-Authors
