7 papers
PMF-CL: Pareto-Minimal-Forgetting Continual Learner for Conflicting Tasks
Srijith Nair, Atilla Eryilmaz, Jia Liu
In the literature, many continual learning (CL) algorithms have been proposed to address the issue of catastrophic forgetting in ML models (i.e., learning new tasks leads to the lo…
Finite-Time Analysis of Gradient Descent for Shallow Transformers
Enes Arda, Semih Cayci, Atilla Eryilmaz
Understanding why Transformers perform so well remains challenging due to their non-convex optimization landscape. In this work, we analyze a shallow Transformer with independe…
An LP-based Sampling Policy for Multi-Armed Bandits with Side-Observations and Stochastic Availability
Ashutosh Soni, Peizhong Ju, Atilla Eryilmaz +1
We study the stochastic multi-armed bandit (MAB) problem where an underlying network structure enables side-observations across related actions. We use a bipartite graph to link ac…
Recurrent Natural Policy Gradient for POMDPs
Semih Cayci, Atilla Eryilmaz
Solving partially observable Markov decision processes (POMDPs) remains a fundamental challenge in reinforcement learning (RL), primarily due to the curse of dimensionality induced…
Optimal Parallel Scheduling under Concave Speedup Functions
Chengzhang Li, Peizhong Ju, Atilla Eryilmaz +1
Efficient scheduling of parallel computation resources across multiple jobs is a fundamental problem in modern cloud/edge computing systems for many AI-based applications. Allocati…
BeST -- A Novel Source Selection Metric for Transfer Learning
Ashutosh Soni, Peizhong Ju, Atilla Eryilmaz +1
One of the most fundamental, and yet relatively less explored, goals in transfer learning is the efficient means of selecting top candidates from a large number of previously train…