13 citations · 38 across the 16 of their papers we have counts for
4 papers · 1 filter
Approximate Probabilistic Inference for Time-Series Data A Robust Latent Gaussian Model With Temporal Awareness
Anton Johansson, Arunselvan Ramaswamy
The development of robust generative models for highly varied non-stationary time series data is a complex yet important problem. Traditional models for time series data prediction…
A Framework for Provably Stable and Consistent Training of Deep Feedforward Networks
Arunselvan Ramaswamy, Shalabh Bhatnagar, Naman Saxena
We present a novel algorithm for training deep neural networks in supervised (classification and regression) and unsupervised (reinforcement learning) scenarios. This algorithm com…
3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems
Adrian Redder, Arunselvan Ramaswamy, Holger Karl
We present Distributed Deep Deterministic Policy Gradient (3DPG), a multi-agent actor-critic (MAAC) algorithm for Markov games. Unlike previous MAAC algorithms, 3DPG is fully distr…
Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis
Arunselvan Ramaswamy, Eyke Hüllermeier
Deep Q-Learning is an important reinforcement learning algorithm, which involves training a deep neural network, called Deep Q-Network (DQN), to approximate the well-known Q-functi…