Analytics Insight

How LLMs are Changing the Way Developers Refactor Code

Overview: LLMs help developers identify and fix complex code issues faster by automatically understanding the full project ...
IEEE

Learnable Non-Uniform Quantization With Sampling-Based Optimization for Variable-Rate Learned Image Compression

Abstract: Variable-rate coding is challenging but indispensable for learned image compression (LIC) that is in nature characterized by nonlinear transform coding (NTC). Existing methods for ...
IEEE

Design Aspects of a Compact Variable Reluctance Resolver

Abstract: Variable reluctance (VR) resolvers are used in electrical drives for position and speed feedback. Their winding-free rotors make them particularly robust and reliable. One example of their ...
Scientific Research Publishing

Amin, M., Song, L., Thorlie, M. A., & Wang, X. (2015). SCAD-Penalized Quantile Regression for High-Dimensional Data Analysis and Variable Selection. Statistica Neerlandica, 69 ...

ABSTRACT: Variable selection using penalized estimation methods in quantile regression models is an important step in screening for relevant covariates. In this paper, we present a one-step estimation ...
Scientific Research Publishing

Abdelmalek, N. N. (1974). On the Discrete Linear L1 Approximation and L1 Solutions of Overdetermined Linear Equations. Journal of Approximation Theory, 11, 38-53.

ABSTRACT: Variable selection using penalized estimation methods in quantile regression models is an important step in screening for relevant covariates. In this paper, we present a one-step estimation ...
GitHub

PReMM: LLM-Based Program Repair for Multi-Method Bugs via Divide and Conquer

PReMM, an LLM-based program repair framework for Multi-Method Bugs. PReMM builds on three core components: the faulty method clustering component to partition the faulty methods into clusters based on ...