Data Driven

Data-driven approaches are revolutionizing scientific research and engineering by leveraging vast datasets to build predictive models and automate complex tasks. Current research focuses on developing and refining algorithms like neural networks (including transformers and graph neural networks), Gaussian processes, and ADMM for diverse applications, ranging from autonomous systems and financial forecasting to scientific discovery and healthcare. This shift towards data-centric methodologies promises to accelerate scientific progress and improve the efficiency and effectiveness of various technological systems, particularly in areas where traditional modeling approaches are limited by complexity or data scarcity.

Papers

February 20, 2023

DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models
Vivian Lin, Kuk Jin Jang, Souradeep Dutta, Michele Caprio, Oleg Sokolsky, Insup Lee
Deep Learning Model Data Driven Distribution Shift ImageNet Benchmark

February 16, 2023

From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms
Omar Besbes, Will Ma, Omar Mouchtaki
Data Driven Decision Making Empirical Risk Minimization Worst Case Contextual Data Newsvendor Problem Real World Performance

February 4, 2023

Rating Sentiment Analysis Systems for Bias through a Causal Lens
Kausik Lakkaraju, Biplav Srivastava, Marco Valtorta
Native Robustness Sentiment Analysis Data Driven Absolute Stance Bias Clear Human Aware Sentiment Orientation

February 3, 2023

Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties
Ashutosh Dutta, Samrat Chatterjee, Arnab Bhattacharya, Mahantesh Halappanavar
Deep Reinforcement Learning Data Driven Defense Algorithm Cyber Defense Autonomous Cyber Adversarial Uncertainty Proactive Cyber Defense

January 31, 2023

January 29, 2023

Data-driven intelligent computational design for products: Method, techniques, and applications
Maolin Yang, Pingyu Jiang, Tianshuo Zang, Yuhao Liu
Financial Application Data Driven Practical Method Barzilai Borwein Technique Computational Design

January 24, 2023

Explainable Data-Driven Optimization: From Context to Decision and Back Again
Alexandre Forel, Axel Parmentier, Thibaut Vidal
Data Driven Context Information Counterfactual Explanation Decision Relevant Information Data Driven Optimization Big Data Problem

January 16, 2023

Sensor data-driven analysis for identification of causal relationships between exposure to air pollution and respiratory rate in asthmatics
D K Arvind, S Maiya
Data Driven Causal Discovery Causal Effect Causal Relationship Air Pollution Respiratory Rate Exposure Data Improved Asthma Control

January 13, 2023

Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition
Nils Wilken, Lea Cohausz, Johannes Schaum, Stefan Lüdtke, Heiner Stuckenschmidt
Data Driven New Combination Goal Recognition Assistance System Planning Perspective Plan Recognition

January 9, 2023

Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control
Adam J. Thorpe, Cyrus Neary, Franck Djeumou, Meeko M. K. Oishi, Ufuk Topcu
Data Driven Kernel Mean Embeddings Nonholonomic System

January 4, 2023

Augmenting data-driven models for energy systems through feature engineering: A Python framework for feature engineering
Sandra Wilfling
Machine Learning Data Driven Data Driven Model Feature Engineering Data Driven Modeling Energy System Software Framework Energy Modeling

January 3, 2023

Task-sequencing Simulator: Integrated Machine Learning to Execution Simulation for Robot Manipulation
Kazuhiro Sasabuchi, Daichi Saito, Atsushi Kanehira, Naoki Wake, Jun Takamatsu, Katsushi Ikeuchi
Data Driven Learning Based Robot Manipulation Student Simulation

December 30, 2022

UBIWEAR: An end-to-end, data-driven framework for intelligent physical activity prediction to empower mHealth interventions
Asterios Bampakis, Sofia Yfantidou, Athena Vakali
End to End Data Driven Health Intervention Interventional Data Self Tracking

December 27, 2022

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach
Ashkan Haji Hosseinloo, Saleh Nabi, Anette Hosoi, Munther A. Dahleh
Data Driven Covid 19 Optimal Policy Residential Building Mechanical Ventilation Airflow Embedded Gas Injection

December 23, 2022

Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge
Ričards Marcinkevičs, Ece Ozkan, Julia E. Vogt
Machine Learning Data Driven Gentle Introduction AI Application Internal Medicine DOCTOR Deep Survival Biomedical Application Much Data

December 13, 2022

December 9, 2022

DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops
Michael Everett, Rudy Bunel, Shayegan Omidshafiei
Data Driven Iterative Refinement Convex Polytope Backward Reachability COLlision Avoidance Neuron Relaxation

December 5, 2022

Learning Imbalanced Data with Vision Transformers
Zhengzhuo Xu, Ruikang Liu, Shuo Yang, Zenghao Chai, Chun Yuan
Vision Transformer Data Driven Long Tailed Recognition Masked Pre Training

Data Driven

Papers

DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models

From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms

Rating Sentiment Analysis Systems for Bias through a Causal Lens

Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties

Distributed sequential federated learning

Learning Data Representations with Joint Diffusion Models

Data-driven intelligent computational design for products: Method, techniques, and applications

Explainable Data-Driven Optimization: From Context to Decision and Back Again

Sensor data-driven analysis for identification of causal relationships between exposure to air pollution and respiratory rate in asthmatics

Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition

Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control

Augmenting data-driven models for energy systems through feature engineering: A Python framework for feature engineering

Task-sequencing Simulator: Integrated Machine Learning to Execution Simulation for Robot Manipulation

UBIWEAR: An end-to-end, data-driven framework for intelligent physical activity prediction to empower mHealth interventions

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach

Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge

Improving Accuracy Without Losing Interpretability: A ML Approach for Time Series Forecasting

Reliable extrapolation of deep neural operators informed by physics or sparse observations

DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops

Learning Imbalanced Data with Vision Transformers