5 papers
Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures
Chenyang Wang, Weizhong Wang, Yinuo Ren +2
iffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve sample quality on task-specific obj…
Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent
Yihang Sun, Huaijin Wang, Patrick Hayden +1
We present the first analytical study of ECD, focusing on the one-dimensional setting for this first installment. We formalize a stochastic ECD dynamics (sECD) with energy-preservi…
Robust equilibria in continuous games: From strategic to dynamic robustness
Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos +1
In this paper, we examine the robustness of Nash equilibria in continuous games, under both strategic and dynamic uncertainty. Starting with the former, we introduce the notion of…
Multi-agent learning under uncertainty: Recurrence vs. concentration
Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos +1
In this paper, we examine the convergence landscape of multi-agent learning under uncertainty. Specifically, we analyze two stochastic models of regularized learning in continuous…
Payoff-based learning with matrix multiplicative weights in quantum games
Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos +1
In this paper, we study the problem of learning in quantum games - and other classes of semidefinite games - with scalar, payoff-based feedback. For concreteness, we focus on the w…