1.7k citations · 2.4k across the 56 of their papers we have counts for
66 papers
Generative Model Proposal based Particle Filtering for Data Assimilation
Chandni Nagda, Mayank Shrivastava, Gudrun Thorkelsdottir +3
Data assimilation models state dynamics conditioned on sequential observations, and has wide-ranging scientific applications. In the filtering setting, the goal is to model the pos…
Neural Exploitation and Exploration of Contextual Bandits
Yikun Ban, Yuchen Yan, Arindam Banerjee +1
In this paper, we study utilizing neural networks for the exploitation and exploration of contextual multi-armed bandits. Contextual multi-armed bandits have been studied for decad…
Improved Algorithms for Neural Active Learning
Yikun Ban, Yuheng Zhang, Hanghang Tong +2
We improve the theoretical and empirical performance of neural-network(NN)-based active learning algorithms for the non-parametric streaming setting. In particular, we introduce tw…
Restricted Strong Convexity of Deep Learning Models with Smooth Activations
Arindam Banerjee, Pedro Cisneros-Velarde, Libin Zhu +1
We consider the problem of optimization of deep learning models with smooth activation functions. While there exist influential results on the problem from the ``near initializatio…
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics
Arindam Banerjee, Tiancong Chen, Xinyan Li +1
Recent years have seen advances in generalization bounds for noisy stochastic algorithms, especially stochastic gradient Langevin dynamics (SGLD) based on stability (Mou et al., 20…
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
Yikun Ban, Yuchen Yan, Arindam Banerjee +1
In this paper, we propose a novel neural exploration strategy in contextual bandits, EE-Net, distinct from the standard UCB-based and TS-based approaches. Contextual multi-armed ba…