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08/24/2023
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory
Risk-sensitive reinforcement learning (RL) has garnered significant atte...
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05/31/2023
There is more to graphs than meets the eye: Learning universal features with self-supervision
We study the problem of learning universal features across multiple grap...
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04/07/2023
Perspectives on AI Architectures and Co-design for Earth System Predictability
Recently, the U.S. Department of Energy (DOE), Office of Science, Biolog...
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02/03/2023
Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties
Development of autonomous cyber system defense strategies and action rec...
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10/05/2022
Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chains
Conformal prediction is a widely used method to quantify uncertainty in ...
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08/03/2022
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach
We develop a novel form of differentiable predictive control (DPC) with ...
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08/01/2022
HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures
Influence maximization aims to select k most-influential vertices or see...
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06/16/2022
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications
Deep reinforcement learning (DRL) has empowered a variety of artificial ...
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05/30/2022
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization
Influence maximization (IM) is a combinatorial problem of identifying a ...
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05/22/2022
Neural Lyapunov Differentiable Predictive Control
We present a learning-based predictive control methodology using the dif...
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03/02/2022
Learning Stochastic Parametric Differentiable Predictive Control Policies
The problem of synthesizing stochastic explicit model predictive control...
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11/08/2021
On the Stochastic Stability of Deep Markov Models
Deep Markov models (DMM) are generative models that are scalable and exp...
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07/13/2021
A Parallel Approximation Algorithm for Maximizing Submodular b-Matching
We design new serial and parallel approximation algorithms for computing...
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02/23/2021
V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities
Weaknesses in computer systems such as faults, bugs and errors in the ar...
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04/21/2018
A 2/3-Approximation Algorithm for Vertex-weighted Matching in Bipartite Graphs
We consider the maximum vertex-weighted matching problem (MVM), in which...
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06/09/2017
AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids
We present AMPS, an augmented matrix approach to update the solution to ...
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04/24/2013
Towards a Networks-of-Networks Framework for Cyber Security
Networks-of-networks (NoN) is a graph-theoretic model of interdependent ...
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12/17/2012
Feature Clustering for Accelerating Parallel Coordinate Descent
Large-scale L1-regularized loss minimization problems arise in high-dime...
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06/27/2012