b'Min Lin'

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 ...

0 Stefan Lionar, et al. ∙

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...

0 Yunqing Zhao, et al. ∙

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...

0 Chao Du, et al. ∙

research

∙ 03/17/2023

A Recipe for Watermarking Diffusion Models

Recently, diffusion models (DMs) have demonstrated their advantageous po...

0 Yunqing Zhao, et al. ∙

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...

0 Tianbo Li, et al. ∙

research

∙ 02/21/2023

On Calibrating Diffusion Probabilistic Models

Recently, diffusion probabilistic models (DPMs) have achieved promising ...

0 Tianyu Pang, et al. ∙

research

∙ 02/09/2023

Better Diffusion Models Further Improve Adversarial Training

It has been recognized that the data generated by the denoising diffusio...

0 Zekai Wang, et al. ∙

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...

0 Weichen Yu, et al. ∙

research

∙ 01/28/2023

Does Federated Learning Really Need Backpropagation?

Federated learning (FL) is a general principle for decentralized clients...

0 Haozhe Feng, et al. ∙

research

∙ 10/14/2022

Mutual Information Regularized Offline Reinforcement Learning

Offline reinforcement learning (RL) aims at learning an effective policy...

6 Xiao Ma, et al. ∙

research

∙ 09/26/2022

Optical Neural Ordinary Differential Equations

Increasing the layer number of on-chip photonic neural networks (PNNs) i...

0 Yun Zhao, et al. ∙

research

∙ 06/21/2022

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

There has been significant progress in developing reinforcement learning...

8 Jiayi Weng, et al. ∙

research

∙ 05/26/2022

O(N^2) Universal Antisymmetry in Fermionic Neural Networks

Fermionic neural network (FermiNet) is a recently proposed wavefunction ...

0 Tianyu Pang, et al. ∙

research

∙ 02/28/2022

CINO: A Chinese Minority Pre-trained Language Model

Multilingual pre-trained language models have shown impressive performan...

1 Ziqing Yang, et al. ∙

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...

0 Tianyu Pang, et al. ∙

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...

0 Xinhsuai Dong, et al. ∙

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...

0 Kun Li, et al. ∙

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...

0 Jin-Yuan Wang, et al. ∙

research

∙ 05/13/2021

Robust Beamforming for Enhancing Security in Multibeam Satellite Systems

This paper proposes a robust beamforming (BF) scheme to enhance physical...

0 Jian Zhang, et al. ∙

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...

0 Jin-Yuan Wang, et al. ∙

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 ...

0 Jin-Yuan Wang, et al. ∙

research

∙ 06/26/2020

Continual Learning from the Perspective of Compression

Connectionist models such as neural networks suffer from catastrophic fo...

0 Xu He, et al. ∙

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 ...

26 Massimo Caccia, et al. ∙

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 ...

0 Jin-Yuan Wang, et al. ∙

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 ...

0 Jin-Yuan Wang, et al. ∙

research

∙ 06/16/2019

Conditional Computation for Continual Learning

Catastrophic forgetting of connectionist neural networks is caused by th...

2 Min Lin, et al. ∙

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...

10 Rahaf Aljundi, et al. ∙

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 ...

0 Jun-Bo Wang, et al. ∙

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...

0 Xiaohuan Wu, et al. ∙

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...

0 Jin-Yuan Wang, et al. ∙

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...

0 Jin-Yuan Wang, et al. ∙

research

∙ 06/22/2018

On the Spectral Bias of Deep Neural Networks

It is well known that over-parametrized deep neural networks (DNNs) are ...

0 Nasim Rahaman, et al. ∙

research

∙ 12/16/2017

A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing

Conventionally, the resource allocation is formulated as an optimization...

0 Jun-Bo Wang, et al. ∙

research

∙ 04/20/2017

Softmax GAN

Softmax GAN is a novel variant of Generative Adversarial Network (GAN). ...

0 Min Lin, et al. ∙

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...

0 Tianqi Chen, et al. ∙

research

∙ 01/18/2015

Correntropy Induced L2 Graph for Robust Subspace Clustering

In this paper, we study the robust subspace clustering problem, which ai...

0 Canyi Lu, et al. ∙

research

∙ 12/19/2014

Purine: A bi-graph based deep learning framework

In this paper, we introduce a novel deep learning framework, termed Puri...

0 Min Lin, et al. ∙

research

∙ 12/16/2013

Network In Network

We propose a novel deep network structure called "Network In Network" (N...

0 Min Lin, et al. ∙

Min Lin

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