640 citations · 685 across the 10 of their papers we have counts for
12 papers
Enhancement of local magnetic ordering temperature due to non-magnetic disorder in anti-Heusler alloy AlMnCu
Soumya Bhowmik, Suvayan Saha, Saikat Debnath +5
Structural disorder is generally regarded as detrimental to magnetism. Since magnetic properties are governed by both the arrangement of magnetic atoms and the crystal environment,…
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification
Hong-You Chen, Jike Zhong, Mingda Zhang +5
Personalized federated learning (PFL) aims to harness the collective wisdom of clients' data while building personalized models tailored to individual clients' data distributions.…
Data-Driven Offline Decision-Making via Invariant Representation Learning
Han Qi, Yi Su, Aviral Kumar +1
The goal in offline data-driven decision-making is synthesize decisions that optimize a black-box utility function, using a previously-collected static dataset, with no active inte…
Efficient Image Representation Learning with Federated Sampled Softmax
Sagar M. Waghmare, Hang Qi, Huizhong Chen +2
Learning image representations on decentralized data can bring many benefits in cases where data cannot be aggregated across data silos. Softmax cross entropy loss is highly effect…
FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients
Jianyu Wang, Hang Qi, Ankit Singh Rawat +4
In classical federated learning, the clients contribute to the overall training by communicating local updates for the underlying model on their private data to a coordinating serv…
Federated Multi-Target Domain Adaptation
Chun-Han Yao, Boqing Gong, Yin Cui +3
Federated learning methods enable us to train machine learning models on distributed user data while preserving its privacy. However, it is not always feasible to obtain high-quali…
Federated Visual Classification with Real-World Data Distribution
Tzu-Ming Harry Hsu, Hang Qi, Matthew Brown
Federated Learning enables visual models to be trained on-device, bringing advantages for user privacy (data need never leave the device), but challenges in terms of data diversity…
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
Tzu-Ming Harry Hsu, Hang Qi, Matthew Brown
Federated Learning enables visual models to be trained in a privacy-preserving way using real-world data from mobile devices. Given their distributed nature, the statistics of the…
Low-Shot Learning with Imprinted Weights
Hang Qi, Matthew Brown, David G. Lowe
Human vision is able to immediately recognize novel visual categories after seeing just one or a few training examples. We describe how to add a similar capability to ConvNet class…
Scene-centric Joint Parsing of Cross-view Videos
Hang Qi, Yuanlu Xu, Tao Yuan +2
Cross-view video understanding is an important yet under-explored area in computer vision. In this paper, we introduce a joint parsing framework that integrates view-centric propos…
A Restricted Visual Turing Test for Deep Scene and Event Understanding
Hang Qi, Tianfu Wu, Mun-Wai Lee +1
This paper presents a restricted visual Turing test (VTT) for story-line based deep understanding in long-term and multi-camera captured videos. Given a set of videos of a scene (s…
Joint Image-Text News Topic Detection and Tracking with And-Or Graph Representation
Weixin Li, Jungseock Joo, Hang Qi +1
In this paper, we aim to develop a method for automatically detecting and tracking topics in broadcast news. We present a hierarchical And-Or graph (AOG) to jointly represent the l…