Amber Srivastava

See my Google Scholar profile for all the publications. Some of the select few are listed below.

Journal

• A. Srivastava, S.M. Salapaka Dynamic Parameters in Sequential Decision Making., Automatica, Journal of IFAC, 2022.
  

• A. Srivastava, R.K. Velicheti, S.M. Salapaka On the choice of Number of Superstates in the Aggregation of Markov Chains., Pattern Recognition Letters, 2022.
  

• A. Srivastava, S.M. Salapaka. Parameterized MDPs and Reinforcement Learning Problems – A Maximum Entropy Principle-Based Framework, IEEE Transactions in Cybernetics, 2021.
  

• A. Srivastava, S.M. Salapaka. Simultaneous Facility Location and Path Optimization in Static and Dynamic Networks, IEEE Transactions on Control of Network Systems, 2020.
  

Preprints on arXiv

• A. Srivastava, S.M. Salapaka Time-Varying Parameterized Sequential Decision Making Problems., arXiv:2201.10273, 2022. Under review in Automatica, IFAC
  

• R.K. Velicheti, A. Srivastava, S.M. Salapaka Design of Experiments with Imputable Feature Data: An Entropy-Based Approach, arXiv:2103.15628, 2021.
  

• A. Srivastava, S.M. Salapaka Inequality Constraints in Facility Location and Other Similar Optimization Problems: An Entropy-Based Approach, arXiv:2002.03505, 2020.
  

Conference Proceedings

• A. Srivastava, S.M. Salapaka On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset. , AAAI Conference on Artificial Intelligence, 2019.
  

• M. Baranwal, A. Srivastava, S.M. Salapaka Multiway k-Cut in Static and Dynamic Graphs: A Maximum Entropy Principle Approach. , IEEE Conference on Decision and Control, 2019.
  

• A. Srivastava, S.M. Salapaka Simultaneous Resource Allocation and Route Optimization in Dynamic Multi-Agent Networks., IEEE Indian Control Conference, 2019.
  

• A. Srivastava, S.M. Salapaka Robustness Anal- ysis for Simultaneous Resource Allocation and Route Optimization Problems., ASME Dynamic Systems and Control COnference, 2017.
  

• A. Srivastava, S.M. Salapaka Combined resource allocation and route optimization in multiagent networks: A scalable approach., IEEE American Control Conference (ACC), 2017.