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08/20/2023
A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability
This paper outlines a natural conversational approach to solving persona...
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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...
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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...
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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...
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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...
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04/28/2023
LAVA: Data Valuation without Pre-Specified Learning Algorithms
Traditionally, data valuation is posed as a problem of equitably splitti...
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02/06/2023
PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition
Emotion recognition is essential in the diagnosis and rehabilitation of ...
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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...
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12/02/2022
On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds
We study the expressibility and learnability of convex optimization solu...
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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...
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11/09/2022
Hyper-Parameter Auto-Tuning for Sparse Bayesian Learning
Choosing the values of hyper-parameters in sparse Bayesian learning (SBL...
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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...
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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...
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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,...
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02/23/2022
Learning Neural Networks under Input-Output Specifications
In this paper, we examine an important problem of learning neural networ...
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02/17/2022
Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs
Multivariate time series forecasting has long received significant atten...
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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...
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11/20/2021
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming
Graph representation learning (GRL) is critical for graph-structured dat...
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10/07/2021
Adversarial Unlearning of Backdoors via Implicit Hypergradient
We propose a minimax formulation for removing backdoors from a given poi...
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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...
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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...
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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...
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06/10/2021
A Unified Framework for Task-Driven Data Quality Management
High-quality data is critical to train performant Machine Learning (ML) ...
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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...
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05/02/2021
Controlling Smart Inverters using Proxies: A Chance-Constrained DNN-based Approach
Coordinating inverters at scale under uncertainty is the desideratum for...
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08/04/2019
Boundary Defense against Cyber Threat for Power System Operation
The operation of power grids is becoming increasingly data-centric. Whil...
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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...
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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...
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10/26/2018
Stability-certified reinforcement learning: A control-theoretic perspective
We investigate the important problem of certifying stability of reinforc...
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12/26/2015
Inverse Reinforcement Learning via Deep Gaussian Process
We propose a new approach to inverse reinforcement learning (IRL) based ...
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06/22/2014