Adaptive Mitigation

Adaptive mitigation focuses on dynamically adjusting strategies to counteract various forms of undesirable events or errors, aiming to minimize their negative impact. Current research emphasizes the use of machine learning, particularly reinforcement learning and Bayesian inference, along with graph neural networks, to develop adaptive systems that predict and respond to these events in real-time. These techniques are being applied across diverse fields, from improving the reliability of supercomputers and quantum computers to mitigating cyber threats and enhancing the robustness of natural language processing models. The ultimate goal is to create more resilient and efficient systems capable of handling unexpected challenges and uncertainties.

Papers

November 9, 2024

StopHC: A Harmful Content Detection and Mitigation Architecture for Social Media Platforms
Ciprian-Octavian Truică, Ana-Teodora Constantinescu, Elena-Simona Apostol
Faulty Negative Mitigation Offensive Content Social Medium Platform Harmful Content Stop or Go Decision Content Detection Adaptive Mitigation Network Immunization

July 23, 2024

Reinforcement Learning-based Adaptive Mitigation of Uncorrected DRAM Errors in the Field
Isaac Boixaderas, Sergi Moré, Javier Bartolome, David Vicente, Petar Radojković, Paul M. Carpenter, Eduard Ayguadé
Reinforcement Learning Limited Field Adaptive Method Error Mitigation Random Access Memory Hardware Error Cray XC40 Supercomputer Adaptive Mitigation

May 23, 2024

Efficient Mitigation of Bus Bunching through Setter-Based Curriculum Learning
Avidan Shah, Danny Tran, Yuhan Tang
Reinforcement Learning Curriculum Learning Sub Optimal Adaptive Mitigation

January 25, 2024

Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation
Jennifer Chien, David Danks
Faulty Negative Mitigation Measurement System High Level Plan Fairness Research Affective State Representational Harm Adaptive Mitigation Algorithmic Harm

August 16, 2023

Adaptive mitigation of time-varying quantum noise
Samudra Dasgupta, Arshag Danageozian, Travis S. Humble
Bayesian Inference Quantum Noise Adaptive Mitigation Adaptive Bayesian Quantum Computing Application benchmaRK

May 31, 2023

SPGNN-API: A Transferable Graph Neural Network for Attack Paths Identification and Autonomous Mitigation
Houssem Jmal, Firas Ben Hmida, Nardine Basta, Muhammad Ikram, Mohamed Ali Kaafar, Andy Walker
Attack Method Transferable Graph Neural Adaptive Mitigation

May 1, 2023

Discover and Cure: Concept-aware Mitigation of Spurious Correlation
Shirley Wu, Mert Yuksekgonul, Linjun Zhang, James Zou
Strong Generalization Inherent Interpretability Spurious Correlation Interpretable Concept Adaptive Mitigation

January 10, 2023

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, Saravan Rajmohan
Domain Knowledge Root Cause Production Incident Incident Management Adaptive Mitigation Cloud Incident

November 3, 2022

An Efficient Approach with Dynamic Multi-Swarm of UAVs for Forest Firefighting
Josy John, K. Harikumar, J. Senthilnath, Suresh Sundaram
Robot Swarm Efficient Approach Adaptive Mitigation Multi Agent Search

February 19, 2022

Data-Driven Mitigation of Adversarial Text Perturbation
Rasika Bhalerao, Mohammad Al-Rubaie, Anand Bhaskar, Igor Markov
Word Embeddings Obfuscation Technique Adaptive Mitigation Adversarial Text Perturbation

Adaptive Mitigation

Papers

StopHC: A Harmful Content Detection and Mitigation Architecture for Social Media Platforms

Reinforcement Learning-based Adaptive Mitigation of Uncorrected DRAM Errors in the Field

Efficient Mitigation of Bus Bunching through Setter-Based Curriculum Learning

Beyond Behaviorist Representational Harms: A Plan for Measurement and Mitigation

Adaptive mitigation of time-varying quantum noise

SPGNN-API: A Transferable Graph Neural Network for Attack Paths Identification and Autonomous Mitigation

Discover and Cure: Concept-aware Mitigation of Spurious Correlation

Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models

An Efficient Approach with Dynamic Multi-Swarm of UAVs for Forest Firefighting

Data-Driven Mitigation of Adversarial Text Perturbation