35 citations · 206 across the 44 of their papers we have counts for
48 papers
Sharp Convergence and Sample Complexity of Policy Mirror Descent for Average-Reward MDPs
Enes Arda, Atilla Eryilmaz
Policy mirror descent (PMD) has a mature finite-time theory in discounted Markov decision processes (MDPs), but less is known in the average-reward setting, a more natural objectiv…
A Comparative Analysis of Attention versus State-Space Models for In-Context Learning
Enes Arda, Semih Cayci, Atilla Eryilmaz
Transformers and state-space models (SSMs) are two prominent sequential learning architectures, yet their comparison remains largely empirical and existing theoretical analyses are…
Communication-Aware Model Distributed Inference via Latent Representation Compression
Peyman Gholami, Theodoros-Thirimachos Davarakis, Teng Li +9
We study optimization of distributed model inference over resource-constrained edge resources. We propose a framework that optimizes the trade-off between model accuracy and commun…
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…
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…
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…