109 citations · 315 across the 34 of their papers we have counts for
11 papers · 1 filter
Defense-friendly Images in Adversarial Attacks: Dataset and Metrics for Perturbation Difficulty
Camilo Pestana, Wei Liu, David Glance +1
Dataset bias is a problem in adversarial machine learning, especially in the evaluation of defenses. An adversarial attack or defense algorithm may show better results on the repor…
Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning
Jie An, Tao Li, Haozhi Huang +6
Extracting effective deep features to represent content and style information is the key to universal style transfer. Most existing algorithms use VGG19 as the feature extractor, w…
Energy Efficient User Clustering, Hybrid Precoding and Power Optimization in Terahertz MIMO-NOMA Systems
Haijun Zhang, Haisen Zhang, Wei liu +3
Terahertz (THz) band communication has been widely studied to meet the future demand for ultra-high capacity. In addition, multi-input multi-output (MIMO) technique and non-orthogo…
Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation
Xiaocong Chen, Chaoran Huang, Lina Yao +3
Interactive recommendation aims to learn from dynamic interactions between items and users to achieve responsiveness and accuracy. Reinforcement learning is inherently advantageous…
Quantized Adam with Error Feedback
Congliang Chen, Li Shen, Haozhi Huang +1
In this paper, we present a distributed variant of adaptive stochastic gradient method for training deep neural networks in the parameter-server model. To reduce the communication…
Progressive Multi-Stage Learning for Discriminative Tracking
Weichao Li, Xi Li, Omar Elfarouk Bourahla +5
Visual tracking is typically solved as a discriminative learning problem that usually requires high-quality samples for online model adaptation. It is a critical and challenging pr…
MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
Yuan Gao, Haoping Bai, Zequn Jie +3
We propose to incorporate neural architecture search (NAS) into general-purpose multi-task learning (GP-MTL). Existing NAS methods typically define different search spaces accordin…
E2EET: From Pipeline to End-to-end Entity Typing via Transformer-Based Embeddings
Michael Stewart, Wei Liu
Entity Typing (ET) is the process of identifying the semantic types of every entity within a corpus. In contrast to Named Entity Recognition, where each token in a sentence is labe…
Towards Photo-Realistic Virtual Try-On by Adaptively GeneratingPreserving Image Content
Han Yang, Ruimao Zhang, Xiaobao Guo +3
Image visual try-on aims at transferring a target clothing image onto a reference person, and has become a hot topic in recent years. Prior arts usually focus on preserving the cha…
Real-time Image Smoothing via Iterative Least Squares
Wei Liu, Pingping Zhang, Xiaolin Huang +3
Edge-preserving image smoothing is a fundamental procedure for many computer vision and graphic applications. There is a tradeoff between the smoothing quality and the processing s…
Graph Inference Learning for Semi-supervised Classification
Chunyan Xu, Zhen Cui, Xiaobin Hong +3
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures. Re…