research
∙
07/18/2023
NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
Remarkable progress has been made in 3D reconstruction from single-view ...
share
research
∙
05/26/2023
On Evaluating Adversarial Robustness of Large Vision-Language Models
Large vision-language models (VLMs) such as GPT-4 have achieved unpreced...
research
∙
05/03/2023
Nonparametric Generative Modeling with Conditional and Locally-Connected Sliced-Wasserstein Flows
Sliced-Wasserstein Flow (SWF) is a promising approach to nonparametric g...
research
∙
03/17/2023
A Recipe for Watermarking Diffusion Models
Recently, diffusion models (DMs) have demonstrated their advantageous po...
research
∙
03/01/2023
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
Kohn-Sham Density Functional Theory (KS-DFT) has been traditionally solv...
research
∙
02/21/2023
On Calibrating Diffusion Probabilistic Models
Recently, diffusion probabilistic models (DPMs) have achieved promising ...
research
∙
02/09/2023
Better Diffusion Models Further Improve Adversarial Training
It has been recognized that the data generated by the denoising diffusio...
research
∙
02/09/2023
Bag of Tricks for Training Data Extraction from Language Models
With the advance of language models, privacy protection is receiving mor...
research
∙
01/28/2023
Does Federated Learning Really Need Backpropagation?
Federated learning (FL) is a general principle for decentralized clients...
research
∙
10/14/2022
Mutual Information Regularized Offline Reinforcement Learning
Offline reinforcement learning (RL) aims at learning an effective policy...
research
∙
09/26/2022
Optical Neural Ordinary Differential Equations
Increasing the layer number of on-chip photonic neural networks (PNNs) i...
research
∙
06/21/2022
EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine
There has been significant progress in developing reinforcement learning...
research
∙
05/26/2022
O(N^2) Universal Antisymmetry in Fermionic Neural Networks
Fermionic neural network (FermiNet) is a recently proposed wavefunction ...
research
∙
02/28/2022
CINO: A Chinese Minority Pre-trained Language Model
Multilingual pre-trained language models have shown impressive performan...
research
∙
02/21/2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
The trade-off between robustness and accuracy has been widely studied in...
research
∙
12/22/2021
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness?
The fine-tuning of pre-trained language models has a great success in ma...
research
∙
10/27/2021
LSTM-RPA: A Simple but Effective Long Sequence Prediction Algorithm for Music Popularity Prediction
The big data about music history contains information about time and use...
research
∙
09/23/2021
Secrecy Capacity Bounds for Visible Light Communications With Signal-Dependent Noise
In physical-layer security, one of the most fundamental issues is the se...
research
∙
05/13/2021
Robust Beamforming for Enhancing Security in Multibeam Satellite Systems
This paper proposes a robust beamforming (BF) scheme to enhance physical...
research
∙
04/12/2021
Hovering UAV-Based FSO Communications: Channel Modelling, Performance Analysis, and Parameter Optimization
Relay-assisted free-space optical (FSO) communication systems are exploi...
research
∙
10/31/2020
Tight Capacity Bounds for Indoor Visible Light Communications With Signal-Dependent Noise
Channel capacity bounds are derived for a point-to-point indoor visible ...
research
∙
06/26/2020
Continual Learning from the Perspective of Compression
Connectionist models such as neural networks suffer from catastrophic fo...
research
∙
03/12/2020
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning
Learning from non-stationary data remains a great challenge for machine ...
research
∙
10/13/2019
On the Secrecy Performance of Random VLC Networks with Imperfect CSI and Protected Zone
This paper investigates the physical-layer security for a random indoor ...
research
∙
06/22/2019
On the Secrecy Rate of Spatial Modulation Based Indoor Visible Light Communications
In this paper, we investigate the physical-layer security for a spatial ...
research
∙
06/16/2019
Conditional Computation for Continual Learning
Catastrophic forgetting of connectionist neural networks is caused by th...
research
∙
03/20/2019
Online continual learning with no task boundaries
Continual learning is the ability of an agent to learn online with a non...
research
∙
10/15/2018
Bandit Inspired Beam Searching Scheme for mmWave High-Speed Train Communications
High-speed trains (HSTs) are being widely deployed around the world. To ...
research
∙
08/29/2018
Joint Doppler and Channel Estimation with Nested Arrays for Millimeter Wave Communications
Channel estimation is essential for precoding/combining in millimeter wa...
research
∙
07/26/2018
Adaptive Spatial Modulation for Visible Light Communications with an Arbitrary Number of Transmitters
As a power and bandwidth efficient modulation scheme, the optical spatia...
research
∙
07/26/2018
Physical-layer Security for Indoor Visible Light Communications: Secrecy Capacity Analysis
This paper investigates the physical-layer security for an indoor visibl...
research
∙
06/22/2018
On the Spectral Bias of Deep Neural Networks
It is well known that over-parametrized deep neural networks (DNNs) are ...
research
∙
12/16/2017
A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing
Conventionally, the resource allocation is formulated as an optimization...
research
∙
04/20/2017
Softmax GAN
Softmax GAN is a novel variant of Generative Adversarial Network (GAN). ...
research
∙
12/03/2015
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
MXNet is a multi-language machine learning (ML) library to ease the deve...
research
∙
01/18/2015
Correntropy Induced L2 Graph for Robust Subspace Clustering
In this paper, we study the robust subspace clustering problem, which ai...
research
∙
12/19/2014
Purine: A bi-graph based deep learning framework
In this paper, we introduce a novel deep learning framework, termed Puri...
research
∙
12/16/2013