17 citations · 60 across the 23 of their papers we have counts for
29 papers
Approximation Algorithms for Dual-Memory Request Scheduling in Disaggregated LLM Inference
Xin Wang, Hong Shen, Hui Tian +1
Disaggregated LLM inference executes the prefill and decode phases on separate resource pools, reducing interference between the two phases. However, this architecture introduces a…
Robust affine point matching via quadratic assignment on Grassmannians
Alexander Kolpakov, Michael Werman
Robust Affine Matching with Grassmannians (RoAM) is a new algorithm to perform affine registration of point clouds. The algorithm is based on minimizing the Frobenius distance betw…
An approach to robust ICP initialization
Alexander Kolpakov, Michael Werman
In this note, we propose an approach to initialize the Iterative Closest Point (ICP) algorithm to match unlabelled point clouds related by rigid transformations. The method is base…
DecisioNet: A Binary-Tree Structured Neural Network
Noam Gottlieb, Michael Werman
Deep neural networks (DNNs) and decision trees (DTs) are both state-of-the-art classifiers. DNNs perform well due to their representational learning capabilities, while DTs are com…
On best uniform approximation of finite sets by linear combinations of real valued functions using linear programming
Steven B. Damelin, Michael Werman
We study the best approximation problem: \[ \displaystyle \min_{α\in \mathbb R^m}\max_{1\leq i\leq n}\left|y_i -\sum_{j=1}^m α_j Γ_j ({\bf x}_i) \right|. \] Here: $Γ:=\left\{Γ_1,..…
Fully Convolutional Fractional Scaling
Michael Soloveitchik, Michael Werman
We introduce a fully convolutional fractional scaling component, FCFS. Fully convolutional networks can be applied to any size input and previously did not support non-integer scal…