Wei Shen

CO2: Consistent Contrast for Unsupervised Visual Representation Learning

2020 · arXiv (Cornell University)

Contrastive learning has been adopted as a core method for unsupervised visual representation learning. Without human annotation, the common practice is to perform an instance discrimination task: Given a query image crop, this task labels …

Multiserver System Configuration Scheme for Profit Maximization

2021

As a promising and valuable IT commercial model, Cloud computing has been paid considerable attention by academia and industry [1], which makes the configuration of storage, computing, and communication resources a common commodity for pay-as-you-go …

SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance

2022 · arXiv (Cornell University)

Ad relevance modeling plays a critical role in online advertising systems including Microsoft Bing. To leverage powerful transformers like BERT in this low-latency setting, many existing approaches perform ad-side computations offline. While efficient, these approaches …

A New Safe-Level Enabled Borderline-SMOTE for Condition Recognition of Imbalanced Dataset

2023 · IEEE Transactions on Instrumentation and Measurement

Machine learning-based classification strategy has been successfully applied in actual industrial monitoring but it is often hindered when the data set is imbalanced. Technically, the misclassification phenomenon, as a serious performance degradation of generalisation ability, …

Human-Instruction-Free LLM Self-Alignment with Limited Samples

2024 · arXiv (Cornell University)

Aligning large language models (LLMs) with human values is a vital task for LLM practitioners. Current alignment techniques have several limitations: (1) requiring a large amount of annotated data; (2) demanding heavy human involvement; (3) …