Search Results for author:
Found 15 papers, 6 papers with code
MetaOpenFOAM: an LLM-based multi-agent framework for CFD
MetaOpenFOAM, as a novel multi-agent collaborations framework, aims to complete CFD simulation tasks with only natural language as input.
Aqulia-Med LLM: Pioneering Full-Process Open-Source Medical Language Models
We construct a large-scale Chinese and English medical dataset for continue pre-training and a high-quality SFT dataset, covering extensive medical specialties.
Extensions to the Proximal Distance Method of Constrained Optimization
The current paper studies the problem of minimizing a loss $f(\boldsymbol{x})$ subject to constraints of the form $\boldsymbol{D}\boldsymbol{x} \in S$, where $S$ is a closed set, convex or not, and $\boldsymbol{D}$ is a matrix that fuses parameters.
High-Performance Statistical Computing in the Computing Environments of the 2020s
To our knowledge, this is the first demonstration of the feasibility of penalized regression of survival outcomes at this scale.
Computation
2-bit Model Compression of Deep Convolutional Neural Network on ASIC Engine for Image Retrieval
Image retrieval utilizes image descriptors to retrieve the most similar images to a given query image.
Anisotropic structural dynamics of monolayer crystals revealed by femtosecond surface x-ray scattering
X-ray scattering is one of the primary tools to determine crystallographic configuration with atomic accuracy.
Materials Science
Orthogonal Trace-Sum Maximization: Applications, Local Algorithms, and Global Optimality
Through a close inspection of Ky Fan's classical result (1949) on the variational formulation of the sum of largest eigenvalues of a symmetric matrix, and a semidefinite programming (SDP) relaxation of the latter, we first provide a simple method to certify global optimality of a given stationary point of OTSM.
Optimization and Control Computation
Matrix Linear Discriminant Analysis
We propose a novel linear discriminant analysis approach for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies.
Provable Convex Co-clustering of Tensors
Our convex co-clustering (CoCo) estimator enjoys stability guarantees and its computational and storage costs are polynomial in the size of the data.
A Novel Co-design Peta-scale Heterogeneous Cluster for Deep Learning Training
Therefore, MiMatrix intrinsically solves the bandwidth bottleneck of central node in parameter server framework that is widely used in distributed DL tasks.
Deep Neural Network Capacity
However, the capacity of deep neural network architecture is still a mystery to the researchers.
ChineseFoodNet: A large-scale Image Dataset for Chinese Food Recognition
In this paper, we introduce a new and challenging large-scale food image dataset called "ChineseFoodNet", which aims to automatically recognizing pictured Chinese dishes.
Algorithms for Fitting the Constrained Lasso
We compare alternative computing strategies for solving the constrained lasso problem.
Proximal Distance Algorithms: Theory and Examples
If $f(\boldsymbol{x})$ is the loss function, and $C$ is the constraint set in a constrained minimization problem, then the proximal distance principle mandates minimizing the penalized loss $f(\boldsymbol{x})+\frac{\rho}{2}\mathop{dist}(x, C)^2$ and following the solution $\boldsymbol{x}_{\rho}$ to its limit as $\rho$ tends to $\infty$.
Optimization and Control 90C59, 90C26, 65K05
Distance Majorization and Its Applications
The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics.
