18 citations · 32 across the 10 of their papers we have counts for
11 papers
Policy Gradient for Continuous-Time Robust Markov Decision Processes
Tanya Veeravalli, David M. Bossens, Atsushi Nitanda
The framework of robust Markov decision processes (RMDPs) allows the design of reinforcement learning agents that satisfy performance guarantees under worst-case transition dynamic…
Slowly Annealed Langevin Dynamics: Theory and Applications to Training-Free Guided Generation
Atsushi Nitanda, Dake Bu, Yueming Lyu +1
We study Slowly Annealed Langevin Dynamics (SALD), a sampler for tracking a path of moving target distributions and approximating the terminal target through time slowdown. We esta…
Revisiting Stochastic Realization Theory using Functional Itô Calculus
Tanya Veeravalli, Maxim Raginsky
This paper considers the problem of constructing finite-dimensional state space realizations for stochastic processes that can be represented as the outputs of a certain type of a…
A Constructive Approach to Function Realization by Neural Stochastic Differential Equations
Tanya Veeravalli, Maxim Raginsky
The problem of function approximation by neural dynamical systems has typically been approached in a top-down manner: Any continuous function can be approximated to an arbitrary ac…
Nonlinear controllability and function representation by neural stochastic differential equations
Tanya Veeravalli, Maxim Raginsky
There has been a great deal of recent interest in learning and approximation of functions that can be expressed as expectations of a given nonlinearity with respect to its random i…
The Twelvefold Way of Non-Sequential Lossless Compression
Taha Ameen ur Rahman, Alton S. Barbehenn, Xinan Chen +27
Many information sources are not just sequences of distinguishable symbols but rather have invariances governed by alternative counting paradigms such as permutations, combinations…
smartSDH: An Experimental Study of Mechanism Based Building Control
Ioannis C. Konstantakopoulos, Kristy A. Hamilton, Yashaswini Murthy +3
As Internet of Things (IoT) technologies are increasingly being deployed, situations frequently arise where multiple stakeholders must reconcile preferences to control a shared res…
Design, Benchmarking and Explainability Analysis of a Game-Theoretic Framework towards Energy Efficiency in Smart Infrastructure
Ioannis C. Konstantakopoulos, Hari Prasanna Das, Andrew R. Barkan +6
In this paper, we propose a gamification approach as a novel framework for smart building infrastructure with the goal of motivating human occupants to reconsider personal energy u…
A Novel Graphical Lasso based approach towards Segmentation Analysis in Energy Game-Theoretic Frameworks
Hari Prasanna Das, Ioannis C. Konstantakopoulos, Aummul Baneen Manasawala +3
Energy game-theoretic frameworks have emerged to be a successful strategy to encourage energy efficient behavior in large scale by leveraging human-in-the-loop strategy. A number o…
Segmentation Analysis in Human Centric Cyber-Physical Systems using Graphical Lasso
Hari Prasanna Das, Ioannis C. Konstantakopoulos, Aummul Baneen Manasawala +3
A generalized gamification framework is introduced as a form of smart infrastructure with potential to improve sustainability and energy efficiency by leveraging humans-in-the-loop…
A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University
Ioannis C. Konstantakopoulos, Andrew R. Barkan, Shiying He +3
The implementation of smart building technology in the form of smart infrastructure applications has great potential to improve sustainability and energy efficiency by leveraging h…