research
∙
06/08/2023
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization
In domain generalization (DG), the target domain is unknown when the mod...
share
research
∙
12/16/2022
SplitGP: Achieving Both Generalization and Personalization in Federated Learning
A fundamental challenge to providing edge-AI services is the need for a ...
research
∙
08/01/2022
Locally Supervised Learning with Periodic Global Guidance
Locally supervised learning aims to train a neural network based on a lo...
research
∙
02/14/2022
Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation
Few-shot learning allows machines to classify novel classes using only a...
research
∙
01/07/2022
GenLabel: Mixup Relabeling using Generative Models
Mixup is a data augmentation method that generates new data points by mi...
research
∙
12/10/2020
Communication-Computation Efficient Secure Aggregation for Federated Learning
Federated learning has been spotlighted as a way to train neural network...
research
∙
10/22/2020
Task-Adaptive Feature Transformer for Few-Shot Segmentation
Few-shot learning allows machines to classify novel classes using only a...
research
∙
03/19/2020
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
Learning novel concepts while preserving prior knowledge is a long-stand...
research
∙
03/18/2020
CAFENet: Class-Agnostic Few-Shot Edge Detection Network
We tackle a novel few-shot learning challenge, which we call few-shot se...
research
∙
03/18/2020
Task-Adaptive Clustering for Semi-Supervised Few-Shot Classification
Few-shot learning aims to handle previously unseen tasks using only a sm...
research
∙
01/29/2020
Cache Allocations for Consecutive Requests of Categorized Contents: Service Provider's Perspective
In wireless caching networks, a user generally has a concrete purpose of...
research
∙
10/14/2019
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks
Recent advances in large-scale distributed learning algorithms have enab...
research
∙
05/16/2019
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Handling previously unseen tasks after given only a few training example...
research
∙
01/16/2019
Coded Matrix Multiplication on a Group-Based Model
Coded distributed computing has been considered as a promising technique...
research
∙
01/11/2019
Coded Distributed Computing over Packet Erasure Channels
Coded computation is a framework which provides redundancy in distribute...
research
∙
07/20/2018
Bi-Directional Cooperative NOMA without Full CSIT
In this paper, we propose bi-directional cooperative non-orthogonal mult...
research
∙
06/29/2018
Dynamic Power Allocation and User Scheduling for Power-Efficient and Low-Latency Communications
In this paper, we propose a joint dynamic power control and user pairing...
research
∙
06/05/2018
Wireless Video Caching and Dynamic Streaming under Differentiated Quality Requirements
This paper considers one-hop device-to-device (D2D)-assisted wireless ca...
research
∙
06/04/2018
Meta Learner with Linear Nulling
We propose a meta learning algorithm utilizing a linear transformer that...
research
∙
01/15/2018
Hierarchical Coding for Distributed Computing
Coding for distributed computing supports low-latency computation by rel...
research
∙
01/08/2018
Explicit Construction of MBR Codes for Clustered Distributed Storage
Capacity of the distributed storage system (DSS) is often discussed in t...
research
∙
01/06/2018
A Class of MSR Codes for Clustered Distributed Storage
Clustered distributed storage models real data centers where intra- and ...
research
∙
10/16/2017
