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12/07/2022
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast Evasion of Non-Degenerate Saddle Points
Gradient-based first-order convex optimization algorithms find widesprea...
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12/05/2022
PowRL: A Reinforcement Learning Framework for Robust Management of Power Networks
Power grids, across the world, play an important societal and economical...
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07/26/2022
Fixed-Time Convergence for a Class of Nonconvex-Nonconcave Min-Max Problems
This study develops a fixed-time convergent saddle point dynamical syste...
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03/02/2022
A Learning Based Framework for Handling Uncertain Lead Times in Multi-Product Inventory Management
Most existing literature on supply chain and inventory management consid...
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12/02/2021
Breaking the Convergence Barrier: Optimization via Fixed-Time Convergent Flows
Accelerated gradient methods are the cornerstones of large-scale, data-d...
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08/17/2021
Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays
Several real-world scenarios, such as remote control and sensing, are co...
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02/13/2020
The Power of Graph Convolutional Networks to Distinguish Random Graph Models: Short Version
Graph convolutional networks (GCNs) are a widely used method for graph r...
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10/28/2019
The Power of Graph Convolutional Networks to Distinguish Random Graph Models
Graph convolutional networks (GCNs) are a widely used method for graph r...
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10/31/2018
On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset
Typically clustering algorithms provide clustering solutions with prespe...
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10/31/2018