$$ \begin{array}{ll} \underset{x \in \mathbb{R}^n}{\min} \quad & \langle c, x \rangle \\ \text{s.t.} \quad & L \leq A x \leq U, \\ & l \leq x \leq u . \end{array ...
An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...
Inverse optimisation and linear programming have emerged as crucial instruments in addressing complex decision-making problems where underlying models must be inferred from observed behaviour. At its ...
Chinese artificial intelligence start-up DeepSeek has ushered in 2026 with a new technical paper, co-authored by founder Liang Wenfeng, that proposes a rethink of the fundamental architecture used to ...
Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...
Renowned mathematician Joel David Hamkins has expressed strong doubts about large language models' utility in mathematical research, calling their outputs "garbage" and "mathematically incorrect".
Abstract: The advent of the global navigation satellite system has greatly enhanced satellite positioning technology, with precise point positioning (PPP) emerging as a prominent technique. Despite ...
Abstract: The fractional order Cole models are the most common form of electrical equivalent circuits (EEC) to model complex impedance (Z) of various dielectric materials like electrodes, sensors, ...
Write down the Linear Program (LP) relaxation of an IP Plot the graphical representation of an IP and find the optimal solution Understand the relationship between optimal solution of an IP and the ...
“Cooking method using wet and dry heats” is a confusing question in Cookie Ham if you are not knowledgeable in cooking. Let’s solve “Cooking method using wet and dry heats” in Cookie Jam Source: ...
This is the official implementation of "Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models". This paper has been accpeted by ...