7 accepted papers
Protecting personal and sensitive information in textual data is increasingly crucial, especially when leveraging large language models (LLMs) that may pose privacy risks due to their API-based access. We introduce a novel approach and pipeline for anonymizing text across arbitrary domains without t…
Knowledge distillation (KD), a technique widely employed in computer vision, has emerged as a de facto standard for improving the performance of small neural networks. However, prevailing KD-based approaches in video tasks primarily focus on designing loss functions and fusing cross-modal informatio…
Weakly-supervised action localization aims to recognize and localize action instancese in untrimmed videos with only video-level labels. Most existing models rely on multiple instance learning(MIL), where the predictions of unlabeled instances are supervised by classifying labeled bags. The MIL-base…
The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims at improving the performance of practical DL implementations in terms of cloud bandwidth consumption, response latency, and data privacy preservation. Focusing on bandwidth efficient edge-cloud collaborative training of DNN-based…
Multiproduct systems are becoming more and more prevalent in modern manufacturing. In this paper, we introduce an application study of optimal control policy in a two-product door manufacturing line at an automotive assembly plant. In such a system, two types of doors for sedans and SUVs are produce
Setup times commonly exist in many flexible manufacturing lines to adjust tools and carry out safety and quality check during product changeovers. In this paper, a Markov chain model is introduced to study flexible manufacturing lines with setups. An aggregation-based recursive procedure is introduc
We introduce a novel scheme to train binary convolutional neural networks (CNNs) -- CNNs with weights and activations constrained to {-1,+1} at run-time. It has been known that using binary weights and activations drastically reduce memory size and accesses, and can replace arithmetic operations wit…