Publications

Under Preparation:

1. An optimal Variance Reduction algorithm for Online Kernel Learning under Nonconvex settings.

Journals:

1. H. Pradhan, K. Rajawat, A. Koppel, "Near-Optimal Kernel approximation using Submodular Set Cover Theory", submitted to IEEE Transactions on Signal Processing.

2. A. Koppel, H. Pradhan, K. Rajawat, "Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck", Statistics and Computing Journal.

3. H. Pradhan, A. S. Bedi, A. Koppel, K. Rajawat, "Adaptive Kernel Learning in Heterogeneous Networks," IEEE Transactions on Signal and Information Processing over Networks.

4. H. Pradhan, R. Budhiraja, K. Rajawat, "Robust Transceiver Design for AF Asymmetric Two-Way MIMO Relaying," IEEE Transactions on Signal Processing, vol. 68, no. 1, pp. 5488-5503, Sept. 2020.

5. H. Pradhan, S. Kalamkar, A. Banerjee, "Sensing-throughput tradeoff in cognitive radio with random arrivals and departures of multiple primary users," IEEE Communications Letters 19 (3), 415-418 

Conferences:

1. H. Pradhan, K. Rajawat, "A Variance Reduced Nonconvex Stochastic Optimization framework for Online Kernel Learning," Asilomar, Nov. 2022.

2. H. Pradhan, A. Koppel, K. Rajawat, "On Submodular Set Cover Problems for Near-Optimal Online Kernel Basis Selection,"  ICASSP, May 2022. (Slides) (Poster)

3. H. Pradhan, A. S. Bedi, A. Koppel, K. Rajawat, "Conservative Multi-agent Online Kernel Learning in Heterogeneous Networks," in Proc. of the Asilomar Conf. on  Signals, Systems, and Computers, Pacific Grove, CA, USA, Nov. 2020. (Slides)

4. H. Pradhan, A. S. Bedi, A. Koppel, K. Rajawat, "Exact nonparametric decentralized online optimization," 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP) (Slides)

5. A. S. Bedi, H. Pradhan, K. Rajawat, "Decentralized Asynchronous Stochastic Gradient Descent: Convergence Rate Analysis,"  2018 International Conference on Signal Processing and Communications (SPCOM)