Abstract: We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted graph ...
Abstract: Sequential convex programming (SCP) is an iterative technique that solves nonconvex optimization problems by considering a sequence of convex subproblems whose solutions eventually converge, ...
Prior to the Middle East conflict, Myanmar’s economy was showing signs of stabilization, but activity remained weak and increasingly strained. The recent fuel shock has become the central macro ...
Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...
Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
Lecturer: Jason Li (jmli@cs). TA: Meredith Pan (shiqip@andrew). Office hours: Meredith Thursdays 4-5pm, Gates 5th floor commons (subject to change); Jason Tuesdays 2-3pm, Gates 5011 Contacting us: ...
I am Professor in the Industrial Engineering and Operations Research department at Columbia University. I received my PhD in Algorithms, Combinatorics and Optimization (ACO) in 2008 from Tepper School ...
As of 2014, I am a software consultant for Duke University on the AWARE Gigapixel Camera, living and working in Pittsburgh. Prior to that I worked for GigaPan. In the naughts I worked for Google and ...
Liuzexian2008/PDAce_and_aPDAce_for_Convex-Concave_Saddle-Point_Problems_with_Nonlinear_Coupling_Term
Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...
There was an error while loading. Please reload this page.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results