Evaluation is a systematic approach to assessing how well a system achie...
In the growing domain of scientific machine learning, in-context operato...
Vertical Federated Learning (VFL) has emerged as one of the most predomi...
This paper introduces a new neural-network-based approach, namely IN-con...
In the realm of search systems, multi-stage cascade architecture is a
pr...
Vertical federated learning (VFL) is a promising category of federated
l...
It is of great significance to estimate the performance of a given model...
Fully Homomorphic Encryption (FHE) is a key technology enabling
privacy-...
Traditional machine learning techniques have been widely used to establi...
Weight decay is one of the most widely used forms of regularization in d...
Emerging six generation (6G) is the integration of heterogeneous wireles...
Trustworthy and reliable data delivery is a challenging task in Wireless...
Security is one of the major concerns in Industrial Wireless Sensor Netw...
5G edge computing enabled Internet of Medical Things (IoMT) is an effici...
Edge enabled Industrial Internet of Things (IIoT) platform is of great
s...
Vertical federated learning (VFL) is attracting much attention because i...
It has been widely observed that large neural networks can be pruned to ...
Federated recommendation is a new notion of private distributed recommen...
AI has provided us with the ability to automate tasks, extract informati...
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently...
In this work, we address multi-modal information needs that contain text...
When trying to apply the recent advance of Natural Language Understandin...
Recent studies on Question Answering (QA) and Conversational QA (ConvQA)...
We present a novel watermarking scheme to verify the ownership of DNN mo...
We propose a simple but effective modification of the discriminators, na...
Many measurements or observations in computer vision and machine learnin...
Intelligent personal assistant systems for information-seeking conversat...
Transformers do not scale very well to long sequence lengths largely bec...
Pre-trained models like BERT (Devlin et al., 2018) have dominated NLP / ...
In this paper, we consider a new framework for particle filtering under ...
The Fokker-Planck (FP) equation governing the evolution of the probabili...
We propose a new method for inferring the governing stochastic ordinary
...
In this work, we formulate a visual dialog as an information flow in whi...
Distributed Machine Learning suffers from the bottleneck of synchronizat...
Community Question Answering (CQA) has become a primary means for people...
Conversational search is one of the ultimate goals of information retrie...
Many information retrieval and natural language processing problems can ...
We propose a Bayesian physics-informed neural network (B-PINN) to solve ...
We demonstrate experimentally the feasibility of applying reinforcement
...
We propose Sparse Sinkhorn Attention, a new efficient and sparse method ...
This paper considers the task of learning how to make a prognosis of a
p...
Personal assistant systems, such as Apple Siri, Google Assistant, Amazon...
Recent years have witnessed the emergence of 3D medical imaging techniqu...
Recent years have witnessed the emergence and increasing popularity of 3...
Consider the following "local" cut-detection problem in a directed graph...
Uncertainty quantification for forward and inverse problems is a central...
Point-cloud is an efficient way to represent 3D world. Analysis of
point...
We propose a potential flow generator with L_2 optimal transport
regular...
Conversational question answering (ConvQA) is a simplified but concrete
...
Conversational search is an emerging topic in the information retrieval
...