Course Description. This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; ...

A technical paper titled “ROVER: RTL Optimization via Verified E-Graph Rewriting” was published by researchers at Intel Corporation and Imperial College London. Abstract: “Manual RTL design and ...

This paper investigates the distributed convex optimization problem (DCOP) based on continuous-time multiagent systems under a state-dependent graph. The objective is to optimize the sum of local cost ...

Many classical problems in graph theory are naturally generalized to GCS, yielding a new class of problems at the interface of combinatorial and convex optimization with a wide variety of applications ...

Optimization problems can be tricky, but they make the world work better. These kinds of questions, which strive for the best way of doing something, are absolutely everywhere. Your phone’s GPS ...

Temporal logic is a concise way of specifying complex tasks. However, motion planning to achieve temporal logic specifications is difficult, and existing methods struggle to scale to complex ...

The team first proposes a convex alternative to transformers’ self-attention mechanism and reformulates model training as a convex optimization problem. The proposed convex reformulation provides ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...