Memristor-based chips could solve demanding optimization problems far faster and with less energy by replacing dense connections with compact memory devices.

A professionally curated list of awesome resources (paper, code, data, etc.) on Deep Graph Anomaly Detection (DGAD), which is the first work to comprehensively and systematically summarize the recent ...

Traditional software engineering approaches reliability as a binary state of uptime and downtime. Modern ML pipelines render this paradigm obsolete. Today, architects must deploy robust fault-tolerant ...

KAIST researchers have developed a safety verification technology that uncovers roughly seven times more hidden ...

By Qu Liu. The Miner School of Computer and Information Sciences is proud to announce a Dissertation Proposal by Qu Liu titled "Efficient and Adaptive Online Learning M ...

Learn how to improve NGS library preparation, reduce bias, and increase sequencing yield with practical strategies for ...

Chenyi Zhu reflects on national parks, while Christopher Leung wonders about internet slang. By The Learning Network A new collection of some of our favorite “What’s Going On in This Picture?” posts, ...

Abstract: Accurate graph similarity is critical for knowledge transfer in VLSI design, enabling the reuse of prior solutions to reduce engineering effort and turnaround time. We propose Pieceformer, a ...

This is a repository for the paper "Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble", accepted by ACM CCS 2025. This is a cleaned ...

Three terms now compete for the same line in AI engineering job descriptions. Prompt engineering is the established one. Loop engineering entered the AI ...

Machine learning (ML) models trained on personal data have been shown to leak information about users. Differential privacy (DP) enables model training with a guaranteed bound on this leakage. Each ...