Search Results for author: Xun Liu

Found 15 papers, 1 papers with code

Apache Submarine: A Unified Machine Learning Platform Made Simple

1 code implementation22 Aug 2021 Kai-Hsun Chen, Huan-Ping Su, Wei-Chiu Chuang, Hung-Chang Hsiao, Wangda Tan, Zhankun Tang, Xun Liu, Yanbo Liang, Wen-Chih Lo, Wanqiang Ji, Byron Hsu, Keqiu Hu, HuiYang Jian, Quan Zhou, Chien-Min Wang

As machine learning is applied more widely, it is necessary to have a machine learning platform for both infrastructure administrators and users including expert data scientists and citizen data scientists to improve their productivity.

BIG-bench Machine Learning

Expectation Learning for Adaptive Crossmodal Stimuli Association

no code implementations23 Jan 2018 Pablo Barros, German I. Parisi, Di Fu, Xun Liu, Stefan Wermter

The human brain is able to learn, generalize, and predict crossmodal stimuli.

PBODL : Parallel Bayesian Online Deep Learning for Click-Through Rate Prediction in Tencent Advertising System

no code implementations4 Jul 2017 Xun Liu, Wei Xue, Lei Xiao, Bo Zhang

Then we extend the model family to a variety of bayesian online models with increasing feature embedding capabilities, such as Sparse-MLP, FM-MLP and FFM-MLP.

Click-Through Rate Prediction

Assessing the Contribution of Semantic Congruency to Multisensory Integration and Conflict Resolution

no code implementations15 Oct 2018 Di Fu, Pablo Barros, German I. Parisi, Haiyan Wu, Sven Magg, Xun Liu, Stefan Wermter

The efficient integration of multisensory observations is a key property of the brain that yields the robust interaction with the environment.

Hybrid Low-order and Higher-order Graph Convolutional Networks

no code implementations2 Aug 2019 FangYuan Lei, Xun Liu, Qingyun Dai, Bingo Wing-Kuen Ling, Huimin Zhao, Yan Liu

With higher-order neighborhood information of graph network, the accuracy of graph representation learning classification can be significantly improved.

General Classification Graph Representation Learning

Conservation-Based Modeling and Boundary Control of Congestion with an Application to Traffic Management in Center City Philadelphia

no code implementations31 Jan 2021 Xun Liu, Hossein Rastgoftar

By classifying the streets as inlets, outlets, and interior nodes, the model predictive control (MPC) method is applied to alleviate the network traffic congestion by optimizing the traffic inflow and outflow across the boundary of the NOIR with consideration of the inner traffic dynamics as a stochastic process.

Management Model Predictive Control

Boundary Control of Traffic Congestion Modeled as a Non-stationary Stochastic Process

no code implementations26 Mar 2021 Xun Liu, Hossein Rastgoftar

The success of the proposed traffic boundary control is demonstrated by simulation of traffic congestion control in Center City Philadelphia.

Management Model Predictive Control

Can AI detect pain and express pain empathy? A review from emotion recognition and a human-centered AI perspective

no code implementations8 Oct 2021 Siqi Cao, Di Fu, Xu Yang, Stefan Wermter, Xun Liu, Haiyan Wu

Furthermore, we discuss challenges for responsible evaluation of cognitive methods and computational techniques and show approaches to future work to contribute to affective assistants capable of empathy.

Emotion Recognition

A trained humanoid robot can perform human-like crossmodal social attention and conflict resolution

no code implementations2 Nov 2021 Di Fu, Fares Abawi, Hugo Carneiro, Matthias Kerzel, Ziwei Chen, Erik Strahl, Xun Liu, Stefan Wermter

Our saliency prediction model was trained to detect social cues, predict audio-visual saliency, and attend selectively for the robot study.

Saliency Prediction

A Concurrent Switching Model for Traffic Congestion Control

no code implementations11 Apr 2022 Hossein Rastgoftar, Xun Liu, Jean-Baptiste Jeannin

We introduce a new conservation-based approach for traffic coordination modeling and control in a network of interconnected roads (NOIR) with switching movement phase rotations at every NOIR junction.

GPNet: Simplifying Graph Neural Networks via Multi-channel Geometric Polynomials

no code implementations30 Sep 2022 Xun Liu, Alex Hay-Man Ng, FangYuan Lei, Yikuan Zhang, Zhengmin Li

Graph Neural Networks (GNNs) are a promising deep learning approach for circumventing many real-world problems on graph-structured data.

Misaligned orientations of 4f optical neural network for image classification accuracy on various datasets

no code implementations5 Oct 2022 Yanbing Liu, Wei Li, Kun Cheng, Xun Liu, Wei Yang

In order to comprehensively investigate the influence caused by the misalignment, we proposed a method for estimating the performance of a 4f-ONN in response to various misalignment in the context of the image classification task. The misalignment in numerical simulation is estimated by manipulating the optical intensity distributions in the fourth focus plane in the 4f system.

Classification Image Classification

The Butterfly Effect of Model Editing: Few Edits Can Trigger Large Language Models Collapse

no code implementations15 Feb 2024 Wanli Yang, Fei Sun, Xinyu Ma, Xun Liu, Dawei Yin, Xueqi Cheng

In this work, we reveal a critical phenomenon: even a single edit can trigger model collapse, manifesting as significant performance degradation in various benchmark tasks.

Benchmarking Model Editing

Ad Recommendation in a Collapsed and Entangled World

no code implementations22 Feb 2024 Junwei Pan, Wei Xue, Ximei Wang, Haibin Yu, Xun Liu, Shijie Quan, Xueming Qiu, Dapeng Liu, Lei Xiao, Jie Jiang

In this paper, we present an industry ad recommendation system, paying attention to the challenges and practices of learning appropriate representations.

Feature Correlation Model Optimization

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