Search Results for author: Zhuo Wang

Found 21 papers, 8 papers with code

Validating Climate Models with Spherical Convolutional Wasserstein Distance

no code implementations26 Jan 2024 Robert C. Garrett, Trevor Harris, Bo Li, Zhuo Wang

The validation of global climate models is crucial to ensure the accuracy and efficacy of model output.

Learning Interpretable Rules for Scalable Data Representation and Classification

1 code implementation22 Oct 2023 Zhuo Wang, Wei zhang, Ning Liu, Jianyong Wang

Rule-based models, e. g., decision trees, are widely used in scenarios demanding high model interpretability for their transparent inner structures and good model expressivity.

Classification

Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today

no code implementations2 Jun 2023 Zhuo Wang, Rongzhen Li, Bowen Dong, Jie Wang, Xiuxing Li, Ning Liu, Chenhui Mao, Wei zhang, Liling Dong, Jing Gao, Jianyong Wang

In this paper, we explore the potential of LLMs such as GPT-4 to outperform traditional AI tools in dementia diagnosis.

Cloud removal Using Atmosphere Model

no code implementations5 Oct 2022 Yi Guo, Feng Li, Zhuo Wang

Cloud removal is an essential task in remote sensing data analysis.

Cloud Removal

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D and Video Salient Object Detection

1 code implementation8 Aug 2022 Wenbo Zhang, Keren Fu, Zhuo Wang, Ge-Peng Ji, Qijun Zhao

Inspired by the fact that depth quality is a key factor influencing the accuracy, we propose an efficient depth quality-inspired feature manipulation (DQFM) process, which can dynamically filter depth features according to depth quality.

object-detection RGB-D Salient Object Detection +2

Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing

1 code implementation CVPR 2022 Zhuo Wang, Zezheng Wang, Zitong Yu, Weihong Deng, Jiahong Li, Tingting Gao, Zhongyuan Wang

A novel Shuffled Style Assembly Network (SSAN) is proposed to extract and reassemble different content and style features for a stylized feature space.

Contrastive Learning Domain Generalization +1

A Simplified System Model for Optical Camera Communication

no code implementations Conference 2021 Anqi Liu, Wenxiao Shi, Wei Liu, Zhuo Wang

Data rate and communication distance are two important criteria for measuring the performance of optical camera communication (OCC) systems.

Scalable Rule-Based Representation Learning for Interpretable Classification

2 code implementations NeurIPS 2021 Zhuo Wang, Wei zhang, Ning Liu, Jianyong Wang

Rule-based models, e. g., decision trees, are widely used in scenarios demanding high model interpretability for their transparent inner structures and good model expressivity.

Classification Representation Learning

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection

1 code implementation5 Jul 2021 Wenbo Zhang, Ge-Peng Ji, Zhuo Wang, Keren Fu, Qijun Zhao

To tackle this dilemma and also inspired by the fact that depth quality is a key factor influencing the accuracy, we propose a novel depth quality-inspired feature manipulation (DQFM) process, which is efficient itself and can serve as a gating mechanism for filtering depth features to greatly boost the accuracy.

object-detection RGB-D Salient Object Detection +1

RRL: A Scalable Classifier for Interpretable Rule-Based Representation Learning

no code implementations1 Jan 2021 Zhuo Wang, Wei zhang, Ning Liu, Jianyong Wang

Rule-based models, e. g., decision trees, are widely used in scenarios demanding high model interpretability for their transparent inner structures and good model expressivity.

Representation Learning

Learning to drive via Apprenticeship Learning and Deep Reinforcement Learning

no code implementations12 Jan 2020 Wenhui Huang, Francesco Braghin, Zhuo Wang

Therefore, we propose an apprenticeship learning in combination with deep reinforcement learning approach that allows the agent to learn the driving and stopping behaviors with continuous actions.

Robotics

Transparent Classification with Multilayer Logical Perceptrons and Random Binarization

1 code implementation10 Dec 2019 Zhuo Wang, Wei zhang, Ning Liu, Jianyong Wang

In this paper, we propose a new hierarchical rule-based model for classification tasks, named Concept Rule Sets (CRS), which has both a strong expressive ability and a transparent inner structure.

Binarization Classification +1

ColluEagle: Collusive review spammer detection using Markov random fields

1 code implementation5 Nov 2019 Zhuo Wang, Runlong Hu, Qian Chen, Pei Gao, Xiaowei Xu

Previous works use review network effects, i. e. the relationships among reviewers, reviews, and products, to detect fake reviews or review spammers, but ignore time effects, which are critical in characterizing group spamming.

PACT: Parameterized Clipping Activation for Quantized Neural Networks

3 code implementations ICLR 2018 Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan

We show, for the first time, that both weights and activations can be quantized to 4-bits of precision while still achieving accuracy comparable to full precision networks across a range of popular models and datasets.

Quantization

Efficient Neural Codes under Metabolic Constraints

no code implementations NeurIPS 2016 Zhuo Wang, Xue-Xin Wei, Alan A. Stocker, Daniel D. Lee

The advantage could be as large as one-fold, substantially larger than the previous estimation.

Optimization and analysis of large scale data sorting algorithm based on Hadoop

no code implementations1 Jun 2015 Zhuo Wang, Longlong Tian, Dianjie Guo, Xiaoming Jiang

If the data is also too big, it will turn back to the first round and keep on.

Distributed, Parallel, and Cluster Computing

Optimal Neural Population Codes for High-dimensional Stimulus Variables

no code implementations NeurIPS 2013 Zhuo Wang, Alan A. Stocker, Daniel D. Lee

We consider solutions for a minimal case where the number of neurons in the population is equal to the number of stimulus dimensions (diffeomorphic).

Vocal Bursts Intensity Prediction

Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss

no code implementations NeurIPS 2012 Zhuo Wang, Alan A. Stocker, Daniel D. Lee

In this manner, we show how the optimal tuning curve depends upon the loss function, and the equivalence of maximizing mutual information with minimizing $L_p$ loss in the limit as $p$ goes to zero.

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