Search Results for author:
Found 12 papers, 1 papers with code
Fine-tuning of diffusion models via stochastic control: entropy regularization and beyond
This paper aims to develop and provide a rigorous treatment to the problem of entropy regularized fine-tuning in the context of continuous-time diffusion models, which was recently proposed by Uehara et al. (arXiv:2402. 15194, 2024).
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
This is an expository article on the score-based diffusion models, with a particular focus on the formulation via stochastic differential equations (SDE).
Contractive Diffusion Probabilistic Models
The key insight is that the contraction in the backward process narrows score matching errors, as well as discretization error.
Trading and wealth evolution in the Proof of Stake protocol
With the increasing adoption of the Proof of Stake (PoS) blockchain, it is timely to study the economy created by such blockchain.
Trading under the Proof-of-Stake Protocol -- a Continuous-Time Control Approach
In particular, we show when a participant is risk-neutral or risk-seeking, corresponding to the risk-adjusted valuation being a martingale or a sub-martingale, the optimal strategy must be to either buy all the time, sell all the time, or first buy then sell, and with both buying and selling executed at full capacity.
Stability of shares in the Proof of Stake Protocol -- Concentration and Phase Transitions
This paper is concerned with the stability of shares in a cryptocurrency where the new coins are issued according to the Proof of Stake protocol.
Asset Selection via Correlation Blockmodel Clustering
Finally, we conduct an empirical analysis to verify the performance of the algorithm.
Simulated annealing from continuum to discretization: a convergence analysis via the Eyring--Kramers law
in cumulative step size), and provide an explicit rate as a function of the model parameters.
Learning an arbitrary mixture of two multinomial logits
In this paper, we consider mixtures of multinomial logistic models (MNL), which are known to $\epsilon$-approximate any random utility model.
Escaping Saddle Points Efficiently with Occupation-Time-Adapted Perturbations
Motivated by the super-diffusivity of self-repelling random walk, which has roots in statistical physics, this paper develops a new perturbation mechanism for optimization algorithms.
On identifiability and consistency of the nugget in Gaussian spatial process models
We formally establish results on the identifiability and consistency of the nugget in spatial models based upon the Gaussian process within the framework of in-fill asymptotics, i. e. the sample size increases within a sampling domain that is bounded.
Spatial Interpolation
Statistics Theory
Statistics Theory
A class of stochastic games and moving free boundary problems
In this paper we propose and analyze a class of $N$-player stochastic games that include finite fuel stochastic games as a special case.
