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We derive the system of differential equations for the gradient flow characterizing the training process of linear in-context learning in full generality. Next, we explore the geometric structure of the gradient flows in two instances,…

Dynamical Systems · Mathematics 2024-12-24 Songtao Lu , Yingdong Lu , Tomasz Nowicki

We applied Dirac distribution, Bose-Einstein distribution, and occasionally Boltzmann-Gibbs distribution in order to determine which is optimal for income distribution on a large pool of countries. The best fit to the data was observed in…

General Finance · Quantitative Finance 2016-03-29 Elvis Oltean , Fedor Kusmartsev

In this article, we discuss a dynamical stochastic model that represents the time evolution of income distribution of a population, where the dynamics develop from an interplay of multiple economic exchanges in the presence of…

Economics · Quantitative Finance 2017-02-28 Maria Letizia Bertotti , Amit K Chattopadhyay , Giovanni Modanese

This paper presents a special type of distributed optimization problems, where the summation of agents' local cost functions (i.e., global cost function) is convex, but each individual can be non-convex. Unlike most distributed optimization…

Optimization and Control · Mathematics 2021-08-16 Yipeng Pang , Guoqiang Hu

A passive scalar is advected by a velocity field, with a nonuniform spatial source that maintains concentration inhomogeneities. For example, the scalar could be temperature with a source consisting of hot and cold spots, such that the mean…

Fluid Dynamics · Physics 2007-12-12 Jean-Luc Thiffeault , G. A. Pavliotis

The scarcity of labeled data is a long-standing challenge for many machine learning tasks. We propose our gradient flow method to leverage the existing dataset (i.e., source) to generate new samples that are close to the dataset of interest…

Machine Learning · Computer Science 2023-11-06 Xinru Hua , Truyen Nguyen , Tam Le , Jose Blanchet , Viet Anh Nguyen

We develop an online gradient algorithm for optimizing the performance of product-form networks through online adjustment of control parameters. The use of standard algorithms for finding optimal parameter settings is hampered by the…

Optimization and Control · Mathematics 2012-08-31 Jaron Sanders , Sem C. Borst , Johan S. H. van Leeuwaarden

Diffusion and flow-based generative models have achieved remarkable success in domains such as image synthesis, video generation, and natural language modeling. In this work, we extend these advances to weight space learning by leveraging…

Machine Learning · Computer Science 2025-10-17 Daniel Saragih , Deyu Cao , Tejas Balaji

The new proposed "energy gradient theory," which physically explains the phenomena of flow instability and turbulent transition in shear flows and has been shown to be valid for parallel flows, is extended to curved flows in this study.…

Fluid Dynamics · Physics 2007-05-23 Hua-Shu Dou

In this paper we present a simplified model of a proportional taxation system where citizens decide whether to pay taxes or evade them. We initially derive a dynamic equation for the fraction of evaders and then present both its critical…

Physics and Society · Physics 2022-06-17 Alessio Emanuele Biondo , Giulio Burgio , Alessandro Pluchino , Damiano Puglisi

Learning rules -- prescriptions for updating model parameters to improve performance -- are typically assumed rather than derived. Why do some learning rules work better than others, and under what assumptions can a given rule be considered…

Machine Learning · Computer Science 2025-11-03 John J. Vastola , Samuel J. Gershman , Kanaka Rajan

Recent works have shown that gradient-update alignment is a powerful signal for modulating optimizer updates, often leading to faster training. We promote this update-wise heuristic as a mathematically grounded principle for selecting and…

Machine Learning · Computer Science 2026-05-08 Jaerin Lee , Kyoung Mu Lee

We introduce the \emph{pipeline intervention} problem, defined by a layered directed acyclic graph and a set of stochastic matrices governing transitions between successive layers. The graph is a stylized model for how people from different…

Computer Science and Game Theory · Computer Science 2020-09-01 Eshwar Ram Arunachaleswaran , Sampath Kannan , Aaron Roth , Juba Ziani

This paper presents a physical perspective on the human migration phenomenon claiming that human social behaviors are somehow but not completely inspired by nature. Human displacement or migration in the world is highly affected by…

Physics and Society · Physics 2022-01-19 Mina Ghanbari , Ghader Rezazadeh

A new framework for portfolio diversification is introduced which goes beyond the classical mean-variance approach and portfolio allocation strategies such as risk parity. It is based on a novel concept called portfolio dimensionality that…

Portfolio Management · Quantitative Finance 2019-09-23 Mathias Barkhagen , Brian Fleming , Sergio Garcia Quiles , Jacek Gondzio , Joerg Kalcsics , Jens Kroeske , Sotirios Sabanis , Arne Staal

We consider fair allocation of indivisible items under an additional constraint: there is an undirected graph describing the relationship between the items, and each agent's share must form a connected subgraph of this graph. This framework…

Computer Science and Game Theory · Computer Science 2017-06-07 Sylvain Bouveret , Katarína Cechlárová , Edith Elkind , Ayumi Igarashi , Dominik Peters

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid…

Systems and Control · Electrical Eng. & Systems 2024-10-22 Adam Lechowicz , Joshua Comden , Andrey Bernstein

In the last decade, a large body of literature has been developed to explain the universal features of inequality in terms of income and wealth. By now, it is established that the distributions of income and wealth in various economies show…

General Finance · Quantitative Finance 2016-11-25 Anindya S. Chakrabarti , Bikas K. Chakrabarti

Transition to turbulence is due to the instability of a laminar flow subject to a disturbance. This complicated problem can be explained using a new proposed energy gradient theory in our previous study. This theory is extended to the…

Chaotic Dynamics · Physics 2007-05-23 Hua-Shu Dou

This paper considers non-smooth optimization problems where we seek to minimize the pointwise maximum of a continuously parameterized family of functions. Since the objective function is given as the solution to a maximization problem,…

Optimization and Control · Mathematics 2026-01-12 Dimitris Boskos , Jorge Cortés , Sonia Martínez