Akshat Kumar - RankMe

120 papers A* 42A 23B 2C 1Misc 2Journal 32Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Hard Constraints: Budget-Conditioned Reachability For Safe Offline Reinforcement Learning. CoRR Janaka Chathuranga Brahmanage, Akshat Kumar
2025	Misc	`conf`	Adaptive Moving Target Defense in Web Applications and Networks using Factored MDP. COMSNETS Megha Bose, Praveen Paruchuri, Akshat Kumar
2025	J	`jnl`	Leveraging Constraint Violation Signals For Action-Constrained Reinforcement Learning. CoRR Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
2025	A*	`conf`	Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning. AAAI Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
2025	C	`conf`	MedEForm: Medical Data Mobile App. SoMeT Shelly Sachdeva, Subhash Bhalla, Nikita Juyal, Akshat Kumar
2025	J	`jnl`	Offline Safe Policy Optimization From Heterogeneous Feedback. CoRR Ze Gong, Pradeep Varakantham, Akshat Kumar
2025	A*	`conf`	Offline Safe Reinforcement Learning Using Trajectory Classification. AAAI Ze Gong, Akshat Kumar, Pradeep Varakantham
2025	A	`conf`	ShipNaviSim: Data-Driven Simulation for Real-World Maritime Navigation. AAMAS Quang Anh Pham, Janaka Chathuranga Brahmanage, Akshat Kumar
2025	J	`jnl`	TraCeS: Trajectory Based Credit Assignment From Sparse Safety Feedback. CoRR Siow Meng Low, Akshat Kumar
2024	J	`jnl`	A Factored MDP Approach To Moving Target Defense With Dynamic Threat Modeling and Cost Efficiency. CoRR Megha Bose, Praveen Paruchuri, Akshat Kumar
2024	—	`conf`	An Adaptive Multi-Objective Optimization on CMOS Two Stage Op-Amp Circuit Synthesis. VDAT Sridhar P, Harish Mallikarjun Kittur, Arghya Korantak, Akshat Kumar
2024	—	`conf`	An Efficient Approach Using Graphical Neural Network for Network Intrusion Detection System. ICCCNT Shailendra Pratap Singh, Abhay Bansal, Akshat Kumar, Prakhar Agrawal, Druhan Singh, Vivashwan Ghosh
2024	—	`conf`	COMEX: Deeply Observing Application Behavior on Real Android Devices. CSET @ USENIX Security Symposium Zeya Umayya, Dhruv Malik, Arpit Nandi, Akshat Kumar, Sareena Karapoola, Sambuddho Chakravarty
2024	A	`conf`	Difference of Convex Functions Programming for Policy Optimization in Reinforcement Learning. AAMAS Akshat Kumar
2024	A	`conf`	Factored MDP based Moving Target Defense with Dynamic Threat Modeling. AAMAS Megha Bose, Praveen Paruchuri, Akshat Kumar
2024	J	`jnl`	FlowPG: Action-constrained Policy Gradient with Normalizing Flows. CoRR Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
2024	J	`jnl`	Leveraging AI Planning For Detecting Cloud Security Vulnerabilities. CoRR Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar
2024	J	`jnl`	Offline Safe Reinforcement Learning Using Trajectory Classification. CoRR Ze Gong, Akshat Kumar, Pradeep Varakantham
2024	J	`jnl`	Safe Reinforcement Learning with Learned Non-Markovian Safety Constraints. CoRR Siow Meng Low, Akshat Kumar
2024	A*	`conf`	Unified Training of Universal Time Series Forecasting Transformers. ICML Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo
2024	J	`jnl`	Unified Training of Universal Time Series Forecasting Transformers. CoRR Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo
2023	B	`conf`	A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. CPAIOR Jihwan Jeong, Scott Sanner, Akshat Kumar
2023	A*	`conf`	FlowPG: Action-constrained Policy Gradient with Normalizing Flows. NeurIPS Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
2023	A	`conf`	Knowledge Compilation for Constrained Combinatorial Action Spaces in Reinforcement Learning. AAMAS Jiajing Ling, Moritz Lukas Schuler, Akshat Kumar, Pradeep Varakantham
2023	A*	`conf`	Learning Deep Time-index Models for Time Series Forecasting. ICML Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi
2023	J	`jnl`	Mean-field games among teams. CoRR Jayakumar Subramanian, Akshat Kumar, Aditya Mahajan
2023	A*	`conf`	Planning and Learning for Non-markovian Negative Side Effects Using Finite State Controllers. AAAI Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, Shlomo Zilberstein
2023	J	`jnl`	Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain. CoRR Gerald Woo, Chenghao Liu, Akshat Kumar, Doyen Sahoo
2023	A*	`conf`	Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects. ICAPS Siow Meng Low, Akshat Kumar, Scott Sanner
2023	J	`jnl`	Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects. CoRR Siow Meng Low, Akshat Kumar, Scott Sanner
2023	A*	`conf`	Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming. AAAI Aravinth Chembu, Scott Sanner, Hassan Khurram, Akshat Kumar
2022	J	`jnl`	Closing the loop: automatically identifying abnormal imaging results in scanned documents. J. Am. Medical Informatics Assoc. Akshat Kumar, Heath Goodrum, Ashley Kim, Carly Stender, Kirk Roberts, Elmer V. Bernstam
2022	A*	`conf`	CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting. ICLR Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi
2022	J	`jnl`	CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting. CoRR Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi
2022	—	`conf`	Constrained Multiagent Reinforcement Learning for Large Agent Population. ECML/PKDD (4) Jiajing Ling, Arambam James Singh, Nguyen Duc Thien, Akshat Kumar
2022	J	`jnl`	DeepTIMe: Deep Time-Index Meta-Learning for Non-Stationary Time-Series Forecasting. CoRR Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi
2022	J	`jnl`	ETSformer: Exponential Smoothing Transformers for Time-series Forecasting. CoRR Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi
2022	A*	`conf`	InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools. CHI Mustafa Doga Dogan, Ahmad Taka, Michael Lu, Yunyi Zhu, Akshat Kumar, Aakar Gupta, Stefanie Müller
2022	J	`jnl`	InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools. CoRR Mustafa Doga Dogan, Ahmad Taka, Michael Lu, Yunyi Zhu, Akshat Kumar, Aakar Gupta, Stefanie Mueller
2022	A*	`conf`	Preface. ICAPS Sylvie Thiébaux, William Yeoh, Akshat Kumar, Pradeep Varakantham
2022	A*	`ed.`	Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, ICAPS 2022, Singapore (virtual), June 13-24, 2022 ICAPS Akshat Kumar, Sylvie Thiébaux, Pradeep Varakantham, William Yeoh
2022	A*	`conf`	Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. AAAI Siow Meng Low, Akshat Kumar, Scott Sanner
2022	J	`jnl`	Sample-efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. CoRR Siow Meng Low, Akshat Kumar, Scott Sanner
2022	J	`jnl`	Shining light on data: Geometric data analysis through quantum dynamics. CoRR Akshat Kumar, Mohan Sarovar
2022	A	`conf`	Trajectory Optimization for Safe Navigation in Maritime Traffic Using Historical Data. CP Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar
2022	A*	`conf`	Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies. IJCAI Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar
2022	J	`jnl`	Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies. CoRR Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar
2021	A	`conf`	Action Selection for Composable Modular Deep Reinforcement Learning. AAMAS Vaibhav Gupta, Daksh Anand, Praveen Paruchuri, Akshat Kumar
2021	A	`conf`	Approximate Difference Rewards for Scalable Multigent Reinforcement Learning. AAMAS Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
2021	A*	`conf`	Integrating Knowledge Compilation with Reinforcement Learning for Routes. ICAPS Jiajing Ling, Kushagra Chandak, Akshat Kumar
2021	A*	`conf`	Learning and Exploiting Shaped Reward Models for Large Scale Multiagent RL. ICAPS Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
2021	J	`jnl`	Manifold learning via quantum dynamics. CoRR Akshat Kumar, Mohan Sarovar
2021	A	`conf`	Ship-GAN: Generative Modeling Based Maritime Traffic Simulator. AAMAS Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar
2020	J	`jnl`	Combining Propositional Logic Based Decision Diagrams with Decision Making in Urban Systems. CoRR Jiajing Ling, Kushagra Chandak, Akshat Kumar
2020	A	`conf`	Hierarchical Multiagent Reinforcement Learning for Maritime Traffic Management. AAMAS Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
2020	A*	`conf`	Reinforcement Learning for Zone Based Multiagent Pathfinding under Uncertainty. ICAPS Jiajing Ling, Tarun Gupta, Akshat Kumar
2019	A*	`conf`	Decision Making for Improving Maritime Traffic Safety Using Constraint Programming. IJCAI Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau
2019	A	`conf`	Graph Based Optimization for Multiagent Cooperation. AAMAS Arambam James Singh, Akshat Kumar
2019	A*	`conf`	Multiagent Decision Making For Maritime Traffic Management. AAAI Arambam James Singh, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
2019	A*	`conf`	Multiagent Decision Making and Learning in Urban Environments. IJCAI Akshat Kumar
2019	A*	`conf`	Resource Constrained Deep Reinforcement Learning. ICAPS Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar
2019	A*	`conf`	Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs. AAAI Tarun Gupta, Akshat Kumar, Praveen Paruchuri
2018	A*	`conf`	Credit Assignment For Collective Multiagent RL With Global Rewards. NeurIPS Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
2018	A*	`conf`	Integrated Cooperation and Competition in Multi-Agent Decision-Making. AAAI Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein
2018	A*	`conf`	Planning and Learning for Decentralized MDPs With Event Driven Rewards. AAAI Tarun Gupta, Akshat Kumar, Praveen Paruchuri
2018	—	`conf`	Planning and Learning for Decentralized MDPs with Event Driven Rewards. AAAI Workshops Tarun Gupta, Akshat Kumar, Praveen Paruchuri
2018	J	`jnl`	Policy Gradient With Value Function Approximation For Collective Multiagent Planning. CoRR Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
2018	J	`jnl`	Resource Constrained Deep Reinforcement Learning. CoRR Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar
2018	A*	`conf`	Resource-Constrained Scheduling for Maritime Traffic Management. AAAI Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau
2018	J	`jnl`	Risk-Sensitive Stochastic Orienteering Problems for Trip Optimization in Urban Environments. ACM Trans. Intell. Syst. Technol. Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh
2017	A	`conf`	A Multi-Agent System for Coordinating Vessel Traffic. AAMAS Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
2017	A*	`conf`	Collective Multiagent Sequential Decision Making Under Uncertainty. AAAI Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
2017	A	`conf`	Coordinating Vessel Traffic to Improve Safety and Efficiency. AAMAS Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
2017	A*	`conf`	Decentralized Planning in Stochastic Environments with Submodular Rewards. AAAI Rajiv Ranjan Kumar, Pradeep Varakantham, Akshat Kumar
2017	A	`conf`	Multiagent Coordination Using Graph Structured Mathematical Optimization. AAMAS Arambam James Singh, Akshat Kumar
2017	—	`conf`	Policy Gradient With Value Function Approximation For Collective Multiagent Planning. NIPS Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
2017	A*	`conf`	Robust Optimization for Tree-Structured Stochastic Network Design. AAAI Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
2016	A	`conf`	Approximate Inference Using DC Programming For Collective Graphical Models. AISTATS Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon
2016	A*	`conf`	Dual Formulations for Optimizing Dec-POMDP Controllers. ICAPS Akshat Kumar, Hala Mostafa, Shlomo Zilberstein
2016	A*	`conf`	Robust Decision Making for Stochastic Network Design. AAAI Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon
2016	A	`conf`	Robust Influence Maximization: (Extended Abstract). AAMAS Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar
2016	J	`jnl`	Robust Optimization for Tree-Structured Stochastic Network Design. CoRR Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
2016	A*	`conf`	Shortest Path Based Decision Making Using Probabilistic Inference. AAAI Akshat Kumar
2016	—	`conf`	Simultaneous Optimization and Sampling of Agent Trajectories over a Network. AAMAS Workshops (Visionary Papers) Hala Mostafa, Akshat Kumar, Hoong Chuin Lau
2016	—	`conf`	Song year prediction using Apache Spark. ICACCI Prakhar Mishra, Ratika Garg, Akshat Kumar, Arpan Gupta, Praveen Kumar
2015	—	`conf`	Decomposition techniques for urban consolidation problems. CASE Duc Thien Nguyen, Hoong Chuin Lau, Akshat Kumar
2015	A*	`conf`	History-Based Controller Design and Optimization for Partially Observable MDPs. ICAPS Akshat Kumar, Shlomo Zilberstein
2015	—	`conf`	Learning and Controlling Network Diffusion in Dependent Cascade Models. WI-IAT (2) Jiali Du, Pradeep Varakantham, Akshat Kumar, Shih-Fen Cheng
2015	A*	`conf`	Message Passing for Collective Graphical Models. ICML Tao Sun, Daniel Sheldon, Akshat Kumar
2015	A	`conf`	Near-Optimal Decentralized Power Supply Restoration in Smart Grids. AAMAS Pritee Agrawal, Akshat Kumar, Pradeep Varakantham
2015	A*	`conf`	Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs. IJCAI Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham
2015	J	`jnl`	Probabilistic Inference Techniques for Scalable Multiagent Decision Making. J. Artif. Intell. Res. Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
2014	A*	`conf`	Near-Optimal Nonmyopic Contact Center Planning Using Dual Decomposition. ICAPS Akshat Kumar, Sudhanshu Shekhar Singh, Pranav Gupta, Gyana R. Parija
2014	A	`conf`	On understanding diffusion dynamics of patrons at a theme park. AAMAS Jiali Du, Akshat Kumar, Pradeep Varakantham
2013	—	`conf`	Approximate Inference in Collective Graphical Models. ICML (3) Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich
2013	A*	`conf`	Automated Generation of Interaction Graphs for Value-Factored Dec-POMDPs. IJCAI William Yeoh, Akshat Kumar, Shlomo Zilberstein
2013	A	`conf`	Collective Diffusion Over Networks: Models and Inference. UAI Akshat Kumar, Daniel Sheldon, Biplav Srivastava
2013	J	`jnl`	Collective Diffusion Over Networks: Models and Inference. CoRR Akshat Kumar, Daniel Sheldon, Biplav Srivastava
2013	—	`conf`	Observer: Assisted Adaptive Tracking Control of an Underactuated Autonomous Underwater Vehicle. AIR Mohan Santhakumar, Gaurav Parchani, Akshat Kumar, Shanmukh Santosh
2013	—	`conf`	Optimization Approaches for Solving Chance Constrained Stochastic Orienteering Problems. ADT Pradeep Varakantham, Akshat Kumar
2013	A*	`conf`	Parameter Learning for Latent Network Diffusion. IJCAI Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein
2012	J	`jnl`	Anytime Planning for Decentralized POMDPs using Expectation Maximization CoRR Akshat Kumar, Shlomo Zilberstein
2012	A*	`conf`	Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning. AAAI Akshat Kumar, Xiaojian Wu, Shlomo Zilberstein
2012	A	`conf`	Message-Passing Algorithms for MAP Estimation Using DC Programming. AISTATS Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
2012	J	`jnl`	Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation CoRR Akshat Kumar, Shlomo Zilberstein
2011	—	`conf`	Influence Diagrams with Memory States: Representation and Algorithms. ADT Xiaojian Wu, Akshat Kumar, Shlomo Zilberstein
2011	A	`conf`	Message-Passing Algorithms for Quadratic Programming Formulations of MAP Estimation. UAI Akshat Kumar, Shlomo Zilberstein
2011	A	`conf`	Message-passing algorithms for large structured decentralized POMDPs. AAMAS Akshat Kumar, Shlomo Zilberstein
2011	A*	`conf`	Scalable Multiagent Planning Using Probabilistic Inference. IJCAI Akshat Kumar, Shlomo Zilberstein, Marc Toussaint
2010	A	`conf`	Anytime Planning for Decentralized POMDPs using Expectation Maximization. UAI Akshat Kumar, Shlomo Zilberstein
2010	—	`conf`	MAP Estimation for Graphical Models by Likelihood Maximization. NIPS Akshat Kumar, Shlomo Zilberstein
2010	A	`conf`	Point-based backup for decentralized POMDPs: complexity and new algorithms. AAMAS Akshat Kumar, Shlomo Zilberstein
2009	—	`conf`	Constraint-based dynamic programming for decentralized POMDPs with structured interactions. AAMAS (1) Akshat Kumar, Shlomo Zilberstein
2009	—	`conf`	Distributed constraint optimization with structured resource constraints. AAMAS (2) Akshat Kumar, Boi Faltings, Adrian Petcu
2009	Misc	`conf`	Dynamic Programming Approximations for Partially Observable Stochastic Games. FLAIRS Akshat Kumar, Shlomo Zilberstein
2009	A*	`conf`	Event-Detecting Multi-Agent MDPs: Complexity and Constant-Factor Approximations. IJCAI Akshat Kumar, Shlomo Zilberstein
2008	A*	`conf`	H-DPOP: Using Hard Constraints for Search Space Pruning in DCOP. AAAI Akshat Kumar, Adrian Petcu, Boi Faltings
2007	—	`conf`	An Artificial Immune System Based Approach for English Grammar Checking. ICARIS Akshat Kumar, Shivashankar B. Nair
2004	J	`jnl`	Tournament versus Fitness Uniform Selection CoRR Shane Legg, Marcus Hutter, Akshat Kumar
2004	B	`conf`	Tournament versus fitness uniform selection. IEEE Congress on Evolutionary Computation Shane Legg, Marcus Hutter, Akshat Kumar