The Founder and Principal Researcher at Gazillion Labs is combining bounded stochastic price modeling, market microstructure, ...

Abstract: This article examines an online distributed optimization problem over an unbalanced digraph, in which a group of nodes in the network tries to collectively search for a minimizer of a ...

When AI assistants make decisions - whether writing code, solving problems, or suggesting improvements - they often fall into patterns of "local thinking", similar to how we might get stuck trying the ...

Collaborative Innovation Center of Advanced Microstructures, National Laboratory of Solid State Microstructure, & School of Physics, Nanjing University, Nanjing 210093, China ...

The difficulties of algorithmic dynamics in highly nonconvex landscapes are central in several research areas, from hard combinatorial optimization to machine learning. However, it is unclear why and ...

Abstract: This talk is based on a joint work with Soheil Behnezhad, Alma Ghafari, and Ronitt Rubinfeld, to appear in STOC'25, https://arxiv.org/abs/2411.08805. We ...

A systematic withdrawal plan refers to monthly withdrawals from an appreciating fund, especially to provide retirement income. This study proposes a stochastic algorithm that outputs the initial ...

The November 2024 core update took three weeks to complete. With the update complete, now is the time to analyze traffic changes. Recovery from ranking drops can take several months with no guaranteed ...

Stochastic gradient descent (SGD), an important optimization method in machine learning, is widely used for parameter estimation especially in online setting where data comes in stream. While this ...