b'Ming Jin'

research

∙ 08/20/2023

A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability

This paper outlines a natural conversational approach to solving persona...

0 Ming Jin, et al. ∙

research

∙ 08/20/2023

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Current literature, aiming to surpass the "Chain-of-Thought" approach, o...

0 Bilgehan Sel, et al. ∙

research

∙ 07/17/2023

Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection

Multivariate time-series anomaly detection is critically important in ma...

0 Yu Zheng, et al. ∙

research

∙ 07/07/2023

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Time series are the primary data type used to record dynamic system meas...

0 Ming Jin, et al. ∙

research

∙ 05/21/2023

Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs

The great learning ability of deep learning models facilitates us to com...

0 Guangsi Shi, et al. ∙

research

∙ 04/28/2023

LAVA: Data Valuation without Pre-Specified Learning Algorithms

Traditionally, data valuation is posed as a problem of equitably splitti...

4 Hoang Anh Just, et al. ∙

research

∙ 02/06/2023

PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition

Emotion recognition is essential in the diagnosis and rehabilitation of ...

0 Ming Jin, et al. ∙

research

∙ 12/04/2022

Winning the CityLearn Challenge: Adaptive Optimization with Evolutionary Search under Trajectory-based Guidance

Modern power systems will have to face difficult challenges in the years...

0 Vanshaj Khattar, et al. ∙

research

∙ 12/02/2022

On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds

We study the expressibility and learnability of convex optimization solu...

0 Ming Jin, et al. ∙

research

∙ 11/19/2022

Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Design

We study risk-sensitive reinforcement learning (RL) based on an entropic...

0 Yuhao Ding, et al. ∙

research

∙ 11/09/2022

Hyper-Parameter Auto-Tuning for Sparse Bayesian Learning

Choosing the values of hyper-parameters in sparse Bayesian learning (SBL...

0 Dawei Gao, et al. ∙

research

∙ 11/01/2022

Recognizing Nested Entities from Flat Supervision: A New NER Subtask, Feasibility and Challenges

Many recent named entity recognition (NER) studies criticize flat NER fo...

0 Enwei Zhu, et al. ∙

research

∙ 10/25/2022

Variational Bayesian Inference Clustering Based Joint User Activity and Data Detection for Grant-Free Random Access in mMTC

Tailor-made for massive connectivity and sporadic access, grant-free ran...

0 Zhaoji Zhang, et al. ∙

research

∙ 10/12/2022

How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?

Given the volume of data needed to train modern machine learning models,...

25 Yi Zeng, et al. ∙

research

∙ 02/23/2022

Learning Neural Networks under Input-Output Specifications

In this paper, we examine an important problem of learning neural networ...

0 Zain ul Abdeen, et al. ∙

research

∙ 02/17/2022

Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs

Multivariate time series forecasting has long received significant atten...

0 Ming Jin, et al. ∙

research

∙ 02/11/2022

From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach

Anomaly detection from graph data is an important data mining task in ma...

0 Yu Zheng, et al. ∙

research

∙ 11/20/2021

Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming

Graph representation learning (GRL) is critical for graph-structured dat...

0 Yizhen Zheng, et al. ∙

research

∙ 10/07/2021

Adversarial Unlearning of Backdoors via Implicit Hypergradient

We propose a minimax formulation for removing backdoors from a given poi...

0 Yi Zeng, et al. ∙

research

∙ 09/08/2021

Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systems

Neural network controllers have become popular in control tasks thanks t...

0 Fangda Gu, et al. ∙

research

∙ 08/23/2021

Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection

Anomaly detection from graph data has drawn much attention due to its pr...

0 Yu Zheng, et al. ∙

research

∙ 07/16/2021

MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition

As an essential element for the diagnosis and rehabilitation of psychiat...

0 Hao Chen, et al. ∙

research

∙ 06/10/2021

A Unified Framework for Task-Driven Data Quality Management

High-quality data is critical to train performant Machine Learning (ML) ...

0 Tianhao Wang, et al. ∙

research

∙ 05/12/2021

Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning

Graph representation learning plays a vital role in processing graph-str...

0 Ming Jin, et al. ∙

research

∙ 05/02/2021

Controlling Smart Inverters using Proxies: A Chance-Constrained DNN-based Approach

Coordinating inverters at scale under uncertainty is the desideratum for...

3 Sarthak Gupta, et al. ∙

research

∙ 08/04/2019

Boundary Defense against Cyber Threat for Power System Operation

The operation of power grids is becoming increasingly data-centric. Whil...

0 Ming Jin, et al. ∙

research

∙ 05/24/2019

Power up! Robust Graph Convolutional Network against Evasion Attacks based on Graph Powering

Graph convolutional networks (GCNs) are powerful tools for graph-structu...

0 Ming Jin, et al. ∙

research

∙ 12/02/2018

Unilateral Left-Tail Anderson Darling Test Based Spectrum Sensing with Laplacian Noise

This paper focuses on spectrum sensing under Laplacian noise. To remit t...

0 Lijuan Jiang, et al. ∙

research

∙ 10/26/2018

Stability-certified reinforcement learning: A control-theoretic perspective

We investigate the important problem of certifying stability of reinforc...

0 Ming Jin, et al. ∙

research

∙ 12/26/2015

Inverse Reinforcement Learning via Deep Gaussian Process

We propose a new approach to inverse reinforcement learning (IRL) based ...

0 Ming Jin, et al. ∙

research

∙ 06/22/2014

Environmental Sensing by Wearable Device for Indoor Activity and Location Estimation

We present results from a set of experiments in this pilot study to inve...

0 Ming Jin, et al. ∙

Ming Jin

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