Search Results for author: Yichen Zhang

Found 40 papers, 7 papers with code

GS-Net: Generalizable Plug-and-Play 3D Gaussian Splatting Module

no code implementations17 Sep 2024 Yichen Zhang, Zihan Wang, Jiali Han, Peilin Li, Jiaxun Zhang, Jianqiang Wang, Lei He, Keqiang Li

3D Gaussian Splatting (3DGS) integrates the strengths of primitive-based representations and volumetric rendering techniques, enabling real-time, high-quality rendering.

OrthoDoc: Multimodal Large Language Model for Assisting Diagnosis in Computed Tomography

no code implementations30 Aug 2024 Youzhu Jin, Yichen Zhang

Computed Tomography (CT) is a non-invasive imaging technique used to capture the internal mechanisms of a patient's condition and is widely utilized.

Computed Tomography (CT) Language Modelling +2

PetalView: Fine-grained Location and Orientation Extraction of Street-view Images via Cross-view Local Search with Supplementary Materials

no code implementations19 Jun 2024 Wenmiao Hu, Yichen Zhang, Yuxuan Liang, Xianjing Han, Yifang Yin, Hannes Kruppa, See-Kiong Ng, Roger Zimmermann

Satellite-based street-view information extraction by cross-view matching refers to a task that extracts the location and orientation information of a given street-view image query by using one or multiple geo-referenced satellite images.

Online Tensor Inference

no code implementations28 Dec 2023 Xin Wen, Will Wei Sun, Yichen Zhang

Recent technological advances have led to contemporary applications that demand real-time processing and analysis of sequentially arriving tensor data.

Decision Making

Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning

no code implementations4 Oct 2023 Weidong Liu, Jiyuan Tu, Yichen Zhang, Xi Chen

In this paper, we develop an online robust policy evaluation procedure, and establish the limiting distribution of our estimator, based on its Bahadur representation.

reinforcement-learning Reinforcement Learning

Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality

no code implementations28 May 2023 Kejie Tang, Weidong Liu, Yichen Zhang, Xi Chen

Stochastic gradient descent with momentum (SGDM) has been widely used in many machine learning and statistical applications.

Uncertainty Quantification

Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose

1 code implementation18 May 2023 Yichen Zhang, Jiehong Lin, Ke Chen, Zelin Xu, YaoWei Wang, Kui Jia

Domain gap between synthetic and real data in visual regression (e. g. 6D pose estimation) is bridged in this paper via global feature alignment and local refinement on the coarse classification of discretized anchor classes in target space, which imposes a piece-wise target manifold regularization into domain-invariant representation learning.

6D Pose Estimation regression +2

Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent

no code implementations30 Dec 2022 Xi Chen, Zehua Lai, He Li, Yichen Zhang

With the fast development of big data, it has been easier than before to learn the optimal decision rule by updating the decision rule recursively and making online decisions.

Decision Making Multi-Armed Bandits

Online Statistical Inference for Matrix Contextual Bandit

no code implementations21 Dec 2022 Qiyu Han, Will Wei Sun, Yichen Zhang

To fill in these gaps, in this work we consider a matrix contextual bandit framework where the true model parameter is a low-rank matrix, and propose a fully online procedure to simultaneously make sequential decision-making and conduct statistical inference.

Decision Making

Adaptive Data Fusion for Multi-task Non-smooth Optimization

no code implementations22 Oct 2022 Henry Lam, Kaizheng Wang, Yuhang Wu, Yichen Zhang

We study the problem of multi-task non-smooth optimization that arises ubiquitously in statistical learning, decision-making and risk management.

Decision Making Management

Distributed Estimation and Inference for Semi-parametric Binary Response Models

no code implementations15 Oct 2022 Xi Chen, Wenbo Jing, Weidong Liu, Yichen Zhang

The development of modern technology has enabled data collection of unprecedented size, which poses new challenges to many statistical estimation and inference problems.

Distributed Computing

Observer-based Leader-following Consensus for Positive Multi-agent Systems Over Time-varying Graphs

no code implementations22 Aug 2022 Ruonan Li, Yichen Zhang, Yutao Tang, Shurong Li

This paper addresses the leader-following consensus problem for discrete-time positive multi-agent systems over time-varying graphs.

BiCo-Net: Regress Globally, Match Locally for Robust 6D Pose Estimation

1 code implementation7 May 2022 Zelin Xu, Yichen Zhang, Ke Chen, Kui Jia

Inspired by the success of point-pair features, the goal of this paper is to recover the 6D pose of an object instance segmented from RGB-D images by locally matching pairs of oriented points between the model and camera space.

6D Pose Estimation Benchmarking +1

Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power Systems

1 code implementation2 Mar 2022 Hantao Cui, Yichen Zhang

The environment leverages the modeling and simulation capability of ANDES and the reinforcement learning (RL) environment OpenAI Gym to enable the prototyping and demonstration of RL algorithms for power systems.

OpenAI Gym reinforcement-learning +2

Towards Visual Question Answering on Pathology Images

no code implementations ACL 2021 Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric Xing, Pengtao Xie

In this paper, we aim to develop a pathological visual question answering framework to analyze pathology images and answer medical questions related to these images.

Decision Making Question Answering +1

Unsupervised data augmentation for object detection

no code implementations30 Apr 2021 Yichen Zhang, Zeyang Song, Wenbo Li

Data augmentation has always been an effective way to overcome overfitting issue when the dataset is small.

Data Augmentation Image Classification +4

Provably Correct Controller Synthesis of Switched Stochastic Systems with Metric Temporal Logic Specifications: A Case Study on Power Systems

no code implementations26 Mar 2021 Zhe Xu, Yichen Zhang

In this paper, we present a provably correct controller synthesis approach for switched stochastic control systems with metric temporal logic (MTL) specifications with provable probabilistic guarantees.

Online Statistical Inference for Stochastic Optimization via Kiefer-Wolfowitz Methods

no code implementations5 Feb 2021 Xi Chen, Zehua Lai, He Li, Yichen Zhang

We first present the asymptotic distribution for the Polyak-Ruppert-averaging type Kiefer-Wolfowitz (AKW) estimators, whose asymptotic covariance matrices depend on the distribution of search directions and the function-value query complexity.

Stochastic Optimization valid

Variance Reduction on General Adaptive Stochastic Mirror Descent

no code implementations26 Dec 2020 Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng

In this work, we investigate the idea of variance reduction by studying its properties with general adaptive mirror descent algorithms in nonsmooth nonconvex finite-sum optimization problems.

Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems

no code implementations29 Nov 2020 Yichen Zhang, Feng Qiu, Tianqi Hong, Zhaoyu Wang, Fangxing Li

Self-healing capability is one of the most critical factors for a resilient distribution system, which requires intelligent agents to automatically perform restorative actions online, including network reconfiguration and reactive power dispatch.

Imitation Learning Reinforcement Learning (RL)

Pathological Visual Question Answering

no code implementations6 Oct 2020 Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric Xing, Pengtao Xie

To deal with the issue that a publicly available pathology VQA dataset is lacking, we create PathVQA dataset.

AI Agent Question Answering +2

Deep Active Learning for Solvability Prediction in Power Systems

no code implementations27 Jul 2020 Yichen Zhang, Jianzhe Liu, Feng Qiu, Tianqi Hong, Rui Yao

Traditional methods for solvability region analysis can only have inner approximations with inconclusive conservatism.

Active Learning

COVID-CT-Dataset: A CT Scan Dataset about COVID-19

17 code implementations30 Mar 2020 Xingyi Yang, Xuehai He, Jinyu Zhao, Yichen Zhang, Shanghang Zhang, Pengtao Xie

Using this dataset, we develop diagnosis methods based on multi-task learning and self-supervised learning, that achieve an F1 of 0. 90, an AUC of 0. 98, and an accuracy of 0. 89.

Computed Tomography (CT) COVID-19 Diagnosis +2

PathVQA: 30000+ Questions for Medical Visual Question Answering

5 code implementations7 Mar 2020 Xuehai He, Yichen Zhang, Luntian Mou, Eric Xing, Pengtao Xie

To achieve this goal, the first step is to create a visual question answering (VQA) dataset where the AI agent is presented with a pathology image together with a question and is asked to give the correct answer.

AI Agent Medical Visual Question Answering +2

Robust Synthesis of Wind Turbine Generators to Support Microgrid Frequency Considering Linearization-Induced Uncertainty

no code implementations5 Mar 2020 Yichen Zhang, Chen Chen, Tianqi Hong, Bai Cui, Bo Chen, Feng Qiu

The capability to switch between grid-connected and islanded modes has promoted adoption of microgrid technology for powering remote locations.

Scheduling

HRank: Filter Pruning using High-Rank Feature Map

2 code implementations CVPR 2020 Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, Ling Shao

The principle behind our pruning is that low-rank feature maps contain less information, and thus pruned results can be easily reproduced.

Network Pruning Vocal Bursts Intensity Prediction

Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints

no code implementations16 Jan 2020 Yichen Zhang, Chen Chen, Guodong Liu, Tianqi Hong, Feng Qiu

In this paper, we introduce a deep learning aided constraint encoding method to tackle the frequency-constraint microgrid scheduling problem.

BIG-bench Machine Learning Scheduling

Training convolutional neural networks with cheap convolutions and online distillation

1 code implementation28 Sep 2019 Jiao Xie, Shaohui Lin, Yichen Zhang, Linkai Luo

The large memory and computation consumption in convolutional neural networks (CNNs) has been one of the main barriers for deploying them on resource-limited systems.

Knowledge Distillation

Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks

no code implementations30 Apr 2019 Yichen Zhang, Shanshan Jia, Yajing Zheng, Zhaofei Yu, Yonghong Tian, Siwei Ma, Tiejun Huang, Jian. K. Liu

The SID is an end-to-end decoder with one end as neural spikes and the other end as images, which can be trained directly such that visual scenes are reconstructed from spikes in a highly accurate fashion.

Decoder

First-order Newton-type Estimator for Distributed Estimation and Inference

no code implementations28 Nov 2018 Xi Chen, Weidong Liu, Yichen Zhang

The key component in our method is the proposal of a computationally efficient estimator of $\Sigma^{-1} w$, where $\Sigma$ is the population Hessian matrix and $w$ is any given vector.

Vocal Bursts Type Prediction

Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks

no code implementations6 Nov 2018 Qi Yan, Yajing Zheng, Shanshan Jia, Yichen Zhang, Zhaofei Yu, Feng Chen, Yonghong Tian, Tiejun Huang, Jian. K. Liu

When a deep CNN with many layers is used for the visual system, it is not easy to compare the structure components of CNNs with possible neuroscience underpinnings due to highly complex circuits from the retina to higher visual cortex.

Transfer Learning

Quantile Regression Under Memory Constraint

no code implementations18 Oct 2018 Xi Chen, Weidong Liu, Yichen Zhang

This paper proposes a computationally efficient method, which only requires an initial QR estimator on a small batch of data and then successively refines the estimator via multiple rounds of aggregations.

Distributed Computing quantile regression

The ALMA Early Science view of FUor/EXor objects. I. Through the looking-glass of V2775 Ori

no code implementations2 Nov 2016 Alice Zurlo, Lucas A. Cieza, Jonathan P. Williams, Hector Canovas, Sebastian Perez, Antonio Hales, Koraljka Mužić, David A. Principe, Dary Ruíz-Rodríguez, John Tobin, Yichen Zhang, Zhaohuan Zhu, Simon Casassus, Jose L. Prieto

We report the detection of a marginally resolved circumstellar disc in the ALMA continuum with an integrated flux of $106 \pm 2$ mJy, characteristic radius of $\sim$ 30 au, inclination of $14. 0^{+7. 8}_{-14. 5}$ deg, and is oriented nearly face-on with respect to the plane of the sky.

Solar and Stellar Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics

Statistical Inference for Model Parameters in Stochastic Gradient Descent

no code implementations27 Oct 2016 Xi Chen, Jason D. Lee, Xin T. Tong, Yichen Zhang

Second, for high-dimensional linear regression, using a variant of the SGD algorithm, we construct a debiased estimator of each regression coefficient that is asymptotically normal.

regression

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