Results 261 to 270 of about 26,173,429 (328)

Frictional Matching Models

Annual Review of Economics, 2011
This article reviews the developments in frictional matching models from 1990 to 2010, exploring how search frictions skew the matches that occur. This research succeeded by exploiting new tools from monotone methods under uncertainty. Seeing how this journey plays out is instructive in itself for economic theory.
Lones Smith
openaire   +4 more sources

A model of random matching [PDF]

Journal of Mathematical Economics, 1992
This paper presents a model of random matching between individuals chosen from large populations. We assume that the populations and the set of encounters are infinite but countable and that the encounters are i.i.d. random variables. Furthermore, the probability distribution on individuals according to which they are chosen for each encounter is ...
Itzhak Gilboa, Akihiko Matsui
openaire   +3 more sources

Invariance, model matching and probability matching

Sankhya A, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Eaton, Morris L., Sudderth, William D.
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Flow-GRPO: Training Flow Matching Models via Online RL

arXiv.org
We propose Flow-GRPO, the first method to integrate online policy gradient reinforcement learning (RL) into flow matching models. Our approach uses two key strategies: (1) an ODE-to-SDE conversion that transforms a deterministic Ordinary Differential ...
Jie Liu, Gongye Liu, Jiajun Liang, Yangguang Li, Jiaheng Liu, Xintao Wang, Pengfei Wan, Di Zhang, Wanli Ouyang   +8 more
semanticscholar   +1 more source

CFG-Zero*: Improved Classifier-Free Guidance for Flow Matching Models

arXiv.org
Classifier-Free Guidance (CFG) is a widely adopted technique in diffusion/flow models to improve image fidelity and controllability. In this work, we first analytically study the effect of CFG on flow matching models trained on Gaussian mixtures where ...
Weichen Fan, Amber Yijia Zheng, Raymond A. Yeh, Ziwei Liu   +3 more
semanticscholar   +1 more source

Gaussian Mixture Flow Matching Models

International Conference on Machine Learning
Diffusion models approximate the denoising distribution as a Gaussian and predict its mean, whereas flow matching models reparameterize the Gaussian mean as flow velocity.
Hansheng Chen, Kai Zhang, Hao Tan, Zexiang Xu, Fujun Luan, Leonidas J. Guibas, Gordon Wetzstein, Sai Bi   +7 more
semanticscholar   +1 more source

Making the most of AI and machine learning in organizations and strategy research: Supervised machine learning, causal inference, and matching models

Strategic Management Journal
We spotlight the use of machine learning in two‐stage matching models to deal with sample selection bias. Recent advances in machine learning have unlocked new empirical possibilities for inductive theorizing.
Jason M. Rathje, R. Katila, Philipp Reineke   +2 more
semanticscholar   +1 more source

DUAL MODEL MATCHING

IFAC Proceedings Volumes, 1991
Abstract In control systems, when two types of characteristic transfer function matrices between the reference inputs and the outputs, and between the conceptual inputs and the outputs respectively are considered, there exist one-to-one corresponding relationships between these characteristic transfer function matrices and those of the controllers ...
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Extended Zeros and Model Matching

SIAM Journal on Control and Optimization, 1991
The authors study the constraints imposed upon the zeros of \(k(z)\)-linear maps \(P(z): U(z)\to Y(z)\) and \(M(z): R(z)\to U(z)\) by reason of the fact tht they satisfy the model matching equation \(T(z)=P(z)M(z)\), in which \(T(z): R(z)\to Y(z)\) is \(k(z)\)-linear as well over the field \(k(z)\) of rational functions in \(z\) having coefficients in ...
Sain, Michael K., Wyman, Bostwick F., Peczkowski, Joseph L.   +2 more
openaire   +1 more source