research
∙
12/05/2022
FedTiny: Pruned Federated Learning Towards Specialized Tiny Models
Neural network pruning has been a well-established compression technique...
share
research
∙
08/05/2022
A Probabilistic Bound for Peak Age of Information Guarantee
This paper considers the distribution of a general peak age of informati...
research
∙
03/22/2021
Server Averaging for Federated Learning
Federated learning allows distributed devices to collectively train a mo...
research
∙
01/14/2021
Edge-Cloud Collaboration Enabled Video Service Enhancement: A Hybrid Human-Artificial Intelligence Scheme
In this paper, a video service enhancement strategy is investigated unde...
research
∙
09/21/2020
ES Attack: Model Stealing against Deep Neural Networks without Data Hurdles
Deep neural networks (DNNs) have become the essential components for var...
research
∙
09/17/2020
Distilled One-Shot Federated Learning
Current federated learning algorithms take tens of communication rounds ...
research
∙
09/16/2020
Asking Complex Questions with Multi-hop Answer-focused Reasoning
Asking questions from natural language text has attracted increasing att...
research
∙
08/31/2020
Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks
Recently web applications have been widely used in enterprises to assist...
research
∙
07/13/2020
PRI-VAE: Principle-of-Relevant-Information Variational Autoencoders
Although substantial efforts have been made to learn disentangled repres...
research
∙
04/27/2020
Application of Deep Interpolation Network for Clustering of Physiologic Time Series
Background: During the early stages of hospital admission, clinicians mu...
research
∙
04/27/2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away
Variational Autoencoder (VAE) is widely used as a generative model to ap...
research
∙
02/21/2020
Multicast eMBB and Bursty URLLC Service Multiplexing in a CoMP-Enabled RAN
This paper is concerned with slicing a radio access network (RAN) for si...
research
∙
01/13/2020
RAN Slicing for Massive IoT and Bursty URLLC Service Multiplexing: Analysis and Optimization
The radio access network (RAN) is regarded as one of the potential propo...
research
∙
12/05/2019
Deep Anomaly Detection in Packet Payload
With the widespread adoption of cloud services, especially the extensive...
research
∙
12/02/2019
Improving Question Generation with Sentence-level Semantic Matching and Answer Position Inferring
Taking an answer and its context as input, sequence-to-sequence models h...
research
∙
12/01/2019
DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction
The cornerstone of computational drug design is the calculation of bindi...
research
∙
11/15/2019
Adaptive Leader-Follower Formation Control and Obstacle Avoidance via Deep Reinforcement Learning
We propose a deep reinforcement learning (DRL) methodology for the track...
research
∙
04/17/2019
A Federated Filtering Framework for Internet of Medical Things
Based on the dominant paradigm, all the wearable IoT devices used in the...
research
∙
05/21/2018
Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation
We propose a hierarchically structured reinforcement learning approach t...
research
∙
05/21/2018
Turbo Learning for Captionbot and Drawingbot
We study in this paper the problems of both image captioning and text-to...
research
∙
02/20/2018
Attentive Tensor Product Learning for Language Generation and Grammar Parsing
This paper proposes a new architecture - Attentive Tensor Product Learni...
research
∙
01/30/2018
Structured Memory based Deep Model to Detect as well as Characterize Novel Inputs
While deep learning has pushed the boundaries in various machine learnin...
research
∙
10/29/2017
A Neural-Symbolic Approach to Natural Language Tasks
Deep learning (DL) has in recent years been widely used in natural langu...
research
∙
09/26/2017
Tensor Product Generation Networks for Deep NLP Modeling
We present a new approach to the design of deep networks for natural lan...
research
∙
09/26/2017
Tensor Product Generation Networks
We present a new tensor product generation network (TPGN) that generates...
research
∙
11/17/2014
Joint Association Graph Screening and Decomposition for Large-scale Linear Dynamical Systems
This paper studies large-scale dynamical networks where the current stat...
research
∙
10/05/2014
Learning Topology and Dynamics of Large Recurrent Neural Networks
Large-scale recurrent networks have drawn increasing attention recently ...
research
∙
07/28/2012