Privacy-Preserving Machine Learning

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3 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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PILLAR: Private Inverted-Index Lexical Lookup for Augmented Retrieval
Sep 28, 2026Truong Son Nguyen, Daniel Blackley, Ni Trieu +1Privacy-Preserving Machine Learning
Arizona State University · Department of Computer Science Arizona State University Tempe, AZ 85281, USA · George Mason University +1
GRIN+: Towards Fast Yet Effective Machine Unlearning for Imbalanced Medical Data
Sep 14, 2026Minghui Huang, Junxiao WangMachine Unlearning Imbalanced Classification
Guangzhou University, China
Quantifying the Value of Privileged Information Using a PAC-Bayesian Approach
Sep 14, 2026Vasily Bokov (aQa, Leiden University, The Netherlands +24Privacy-Preserving Machine Learning Pac-Bayesian Theory
Correlation-Guided Fast Machine Unlearning via Hessian Analysis
Sep 14, 2026Ayushi Thakur, Ruchir Gupta, Amit Kumar Jaiswal +1Machine Unlearning Privacy-Preserving Machine Learning
Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University) Varanasi, India · Halmstad University, Sweden
Performative Privacy: When Differential Privacy Maximizes Utility
Aug 28, 2026Uddalak Mukherjee, Edwige Cyffers, Yann ChevaleyreStandard Differential-Privacy Privacy-Preserving Machine Learning
Dauphine PSL · CNRS Dauphine PSL
PACE: Primitive-Aware Code Evolution for Automated Algorithm Design
Aug 7, 2026Zhuoliang Xie, Ruihao Zheng, Xiang Xu +2Evolutionary Search Evolutionary Optimization
1Southern University of Science and Technology · 2Shenzhen University
TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement
Jul 30, 2026Cheng WeiModel-Agnostic Defense Privacy-Preserving Machine Learning
Honor Device Co., Ltd., Shenzhen, China
BettiSplit: Topology-Guided Privacy-Aware Split Learning Against Feature Inversion and Gradient Leakage
Jul 27, 2026Akarsh K. Nair, Muhammad Arifur Rahman, David Brown +1Privacy-Preserving Machine Learning
Department of Computer Science Nottingham Trent University Nottingham, United Kingdom · Information and Computer Science Department SDAIA–KFUPM Joint Research Center for AI Interdisciplinary Research Center for Biosystems and Machines King Fahd University of Petroleum & Minerals Dhahran 31261, Saudi Arabia
Certified in Theory, Broken in Practice: Assumption Gaps in Cryptographic Model Certification
Jul 23, 2026Carter Luck, Olive Franzese-McLaughlin, Elisaweta Masserova +3Zero-Knowledge Proofs Privacy-Preserving Machine Learning
University of Massachusetts Amherst · Vector Institute · University of Toronto +3
Publicly-Verifiable Certificates for Statistical Algorithms
Jul 17, 2026Michael Ngo, Michael P. KimZero-Knowledge Proofs Certificates
MIT · Research completed while at Cornell University, supported by the Bowers Undergraduate Research Experience (BURE) and the Dean Archer Undergraduate Research Program. · Cornell University
Signal-Guided Optimization for Machine Unlearning
Jul 13, 2026Xujia Li, Dan Li, Jian Lou +1Machine Unlearning Unlearning Method
University of Science and Technology of China · Sun Yat-sen University
Equivariant Quantum Clustering with Differential Privacy: Parameter-Efficient Privacy-Preserving Analysis Across Heterogeneous Sensitive Datasets
Jul 9, 2026B. M. Taslimul Haq, Md Arifur Rahman, Tawfiq Al Islam Foysal +2Privacy-Preserving Machine Learning Clustering
Department of Information Systems, Central Michigan University, Mount Pleasant, MI, USA. · Department of Computer and Information Sciences, Trine University, Angola, IN, USA. · Department of Computer Science and Engineering, American International University–Bangladesh (AIUB), Dhaka, Bangladesh. +2
Trustworthy Machine Learning through the Lens of Combinatorial Optimization: Survey and Research Perspectives
Jul 8, 2026Thibaut Vidal, Julien FerryTrustworthy Artificial Intelligence Provable Guarantees
CIRRELT & SCALE-AI Chair in Data-Driven Supply Chains, Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Montreal, Canada
Privacy-Preserving and Verifiable Approximate Distributed Coded Computing
Jul 2, 2026Xavier Martínez-Luaña, Alba Gude-Santos, Manuel Fernández-Veiga +1Privacy-Preserving Machine Learning Federated Learning
Galician Research and Development Center in Advanced Telecommunications (GRADIANT) Estrada do Vilar, 56-58, Vigo, 36214, Spain · atlanTTic, Information & Computing Lab (ICLAB), Telecommunication Engineering School, Universidade de Vigo Vigo, 36310, Spain
TabPATE: Differentially Private Tabular In-Context Learning Without Public Data
Jun 30, 2026Dariush Wahdany, Matthew Jagielski, Jesse C. Cresswell +2Privacy-Preserving Machine Learning Membership Inference Attacks
CISPA · Anthropic · Layer 6 AI
TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems
Jun 24, 2026Erdenebileg Batbaatar, Young YoonFederated Learning Privacy-Preserving Machine Learning
Neouly, Republic of Korea · Department of Computer Engineering, Hongik University, Republic of Korea
DFMU: Data-Frugal Machine Unlearning
Jun 24, 2026Sajith U, Prateek KeserwaniMachine Unlearning Unlearning Method
Samsung R&D Institute India-Bangalore, India
EmotionAI: A Privacy-Preserving Computational Intelligence Pipeline for Speech-Emotion-Grounded Conversational Analysis
Jun 22, 2026Wai Laam Mak, Isibor Kennedy Ihianle, Pedro MachadoText Corpora Privacy-Preserving Machine Learning
School of Science and Technology, Nottingham Trent University, Nottingham, UK
Quantum ring all-reduce: communication and privacy advantages for distributed learning
Jun 18, 2026María Gragera Garcés, Lirandë PiraQuantum Learning Post-Quantum Cryptography
University of Edinburgh, Edinburgh, United Kingdom · Centre for Quantum Technologies, National University of Singapore, Singapore
The Art of Mixology: Mixup-based Obfuscation for Privacy-Preserving Split Learning in Large Language Models
Jun 15, 2026Chen Chen, Xiang Gao, Xianshun Wang +6Privacy-Preserving Machine Learning Obfuscation
College of Computing and Data Science, Nanyang Technological University, Singapore · School of Cyber Science and Engineering, Wuhan University, China
TrustErase: Auditable Instant Machine Unlearning with Passport-Embedded Representations
Jun 15, 2026Rutger Hendrix, Leonardo G. Russo, Concetto Spampinato +2Machine Unlearning Exact Unlearning
University of Catania Catania, Italy
To forget is to preserve: Machine Unlearning for 3D medical image segmentation
Jun 15, 2026Nitesh Kumar Singh, Akhilesh Singh, Arjun AroraMachine Unlearning Exact Unlearning
School of Computer Science UPES, University of Tomorrow Dehradun, India.
A Privacy-Preserving Framework Using Remote Data Science for Inter-Institutional Student Retention Prediction
Jun 11, 2026John Fields, K M Sajjadul Islam, Ruchitha Thota +2Privacy-Preserving Framework Privacy-Preserving Machine Learning
Business Analytics Concordia University Wisconsin · Computer Science Marquette University · Computer Science Concordia University Wisconsin +1
Federated continual learning: A comprehensive survey on lifelong and privacy-preserving learning over distributed and non-stationary data
Jun 9, 2026Masoume Gholizade, Fabrizio Ruffini, Pietro Ducange +1Federated Learning Replay-Based Continual Learning
Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, Pisa, 56122, Italy
Data-aware Static Analysis: Improving Detection of Semantic Faults in Machine Learning Code Using Data Characteristics
Jun 8, 2026Willem Meijer, Kristian Sandahl, Dániel VarróProgram Analysis Mle-Bench Lite
Linköping University, Linköping, Sweden
OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework
Jun 7, 2026Chenhan Jin, Shengze Xu, Qingsong Wang +3Structured Pruning Privacy-Preserving Machine Learning
The Chinese University of Hong Kong · Xiangtan University · University of Utah +3
Detecting and Mitigating Bias by Treating Fairness as a Symmetry Operation
Jun 2, 2026Nishit SinghAlgorithmic Fairness Biases
Birla Institute of Technology and Science, Pilani.
How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning
Jun 1, 2026Jiangwei Chen, Xinyuan Niu, Rachael Hwee Ling Sim +3Machine Unlearning Catastrophic Forgetting
Department of Computer Science, National University of Singapore, Singapore · Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore · Centre for Frontier AI Research, Agency for Science, Technology and Research, Singapore
Primitive Subspaces Mediate Few-Shot Transfer in VLAs
May 29, 2026Anya Singh, Cabrel Happi, Jai Relan +2Few-Shot Learning Subspace
Relling Systems
Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent
May 27, 2026Guillaume Larue, Louis-Adrien Dufrène, Quentin Lampin +2Two-Layer Neural Networks High-Dimensional
Orange Research, Meylan, France · Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France · Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France.
Geometry of Relaxed Fair Regression: A Unified Framework for Aware and Unaware Settings
May 27, 2026M. Generali Lince, V. Divol, R. Flamary +2Algorithmic Fairness Disparities
Inria, Soda team · CREST, ENSAE, IP Paris · Inria, Fairplay joint team +1
Nonlinear Data Integration via Kernel Methods for Data Collaboration Analysis
May 26, 2026Yamato Suetake, Yuta Kawakami, Shunnosuke Ikeda +1Kernel Method Dimensionality Reduction
Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Ibaraki, Japan · Institute of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan
Practical Anonymous Two-Party Gradient Boosting Decision Tree
May 26, 2026Chenyu Huang, Fan Zhang, Minxin Du +6Privacy-Preserving Machine Learning Homomorphic Encryption
Tencent · Hong Kong Polytechnic University · Chinese University of Hong Kong +1
Unlocking Apple's Private Cloud Compute: An Analysis of Privacy-Preserving Artificial Intelligence
May 22, 2026Yannik Dittmar, Marvin Jerome Stephan, Thomas Völkl +2Privacy-Preserving Framework Privacy-Preserving Machine Learning
Hasso Plattner Institute, University of Potsdam Potsdam, Germany · TU Darmstadt, Secure Mobile Networking Lab Darmstadt, Germany · TU Darmstadt, Secure Mobile Networking Lab, Darmstadt, Germany +1
FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data
May 18, 2026Nuredin Ali Abdelkadir, Anjali Ratnam, Zeerak Talat +1Privacy-Preserving Machine Learning Federated Learning
University of Minnesota · University of Edinburgh
MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification
May 14, 2026Weisen Jiang, Shuhao Chen, Sinno Jialin PanPrivacy-Preserving Machine Learning Training Data
Department of Computer Science and Engineering, The Chinese University of Hong Kong · Department of Computer Science and Engineering, Hong Kong University of Science and Technology · Department of Computer Science and Engineering, Southern University of Science and Technology
Keyed Nonlinear Transform: Lightweight Privacy-Enhancing Feature Sharing for Medical Image Analysis
May 13, 2026Haebom Lee, Gyeongjung KimPrivacy-Preserving Machine Learning Medical Images
OOLU Soft Co., Ltd.
LightSplit: Practical Privacy-Preserving Split Learning via Orthogonal Projections
May 13, 2026Mert Cihangiroglu, Alessandro Pegoraro, Phillip Rieger +2Privacy-Preserving Machine Learning Singular Learning Theory
University of Pavia · 2Technical University of Darmstadt
Fair Conformal Classification via Learning Representation-Based Groups
May 12, 2026Senrong Xu, Yanke Zhou, Yuhao Tan +5Conformal Inference Algorithmic Fairness
State Key Lab of Novel Software Technology, Nanjing University, China · ETH Zürich · Birkbeck, University of London
Privacy-Preserving Distributed Learning in IoT Systems: A Unified Threat Model and Evaluation Framework
May 10, 2026John Cartmell, Alexander WilliamsPrivacy-Preserving Machine Learning Internet Of Thing
Department of Electrical Engineering and Computer Science
Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
May 4, 2026Judith Sáinz-Pardo Díaz, Álvaro López GarcíaPrivacy-Preserving Machine Learning Federated Learning
Privacy-Preserving Federated Learning via Differential Privacy and Homomorphic Encryption for Cardiovascular Disease Risk Modeling
Apr 30, 2026Gaurang Sharma, Juha Pajula, Aada Illikainen +4Privacy-Preserving Machine Learning Homomorphic Encryption
VTT Technical Research Centre of Finland Ltd, 33720, Tampere, Finland · VTT Technical Research Centre of Finland Ltd, 02150, Espoo, Finland · Solita Oy, 00100 Helsinki, Finland +1
Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization
Apr 28, 2026Teetat Pipattaratonchai, Aueaphum AueawatthanaphisutChemical Process Systems Federated Learning
Science Math Triamudom Suksa Bangkok, Thailand · School of Information, Computer, and Communication Technology Sirindhorn International Institute of Technology, Thammasat University Pathum Thani, Thailand
Laplace-Bridged Randomized Smoothing for Fast Certified Robustness
Apr 27, 2026Miao Lin, MD Saifur Rahman Mazumder, Feng Yu +2Smoothing Noise-Aware
Department of Computer Science, Old Dominion University, Norfolk, VA, USA · Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX, USA · School of Cybersecurity, Old Dominion University, Norfolk, VA, USA
Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption
Apr 25, 2026Alexandre Marques, Beatriz Sá, Rui Botelho +1Privacy-Preserving Machine Learning Homomorphic Encryption
ISEP, School of Engineering, Polytechnic of Porto, Porto, Portugal · GECAD, Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal
Fairness Constraints in High-Dimensional Generalized Linear Models
Apr 17, 2026Yixiao Lin, James BoothAlgorithmic Fairness Privacy-Preserving Machine Learning
aDepartment of Statistics and Data Science, Cornell University
Federated Computation of ROC and PR Curves
Oct 6, 2025Xuefeng Xu, Graham CormodePrivacy-Preserving Machine Learning Receiver Operating Characteristic Area Under The Curve
University of Warwick
Efficient Unlearning with Privacy Guarantees
Jul 7, 2025Josep Domingo-Ferrer, Najeeb Jebreel, David SánchezMachine Unlearning Privacy-Preserving Machine Learning
1CYBERCAT (Center for Cybersecurity Research of2026 Catalonia), ComSCIAM-Center for Computational Science and Applied Mathematics, Department of Computer EngineeringJun and Mathematics, Universitat Rovira i Virgili, Av. Pa¨ısos26 Catalans 26, E-43007 Tarragona, Catalonia
Tuning without Peeking: Provable Generalization Bounds and Robust LLM Post-Training
Jul 2, 2025Ismail Labiad, Mathurin Videau, Matthieu Kowalski +4Privacy-Preserving Machine Learning Black-Box Optimization
Meta FAIR · Université Paris-Saclay · LISN, Inria, CNRS +2
A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning
Jul 24, 2023Spencer Giddens, Yiwang Zhou, Kevin R. Krull +3Empirical Risk Minimization Privacy-Preserving Machine Learning
University of Notre Dame, Notre Dame, IN 46556, USA · St. Jude Children’s Research Hospital, Memphis, TN 38138, USA · University of Michigan, Ann Arbor, MI 48109, USA
Privacy-Preserving Logistic Regression Training with A Faster Gradient Variant
Jan 26, 2022John ChiangPrivacy-Preserving Machine Learning Gradient-Based Attacks

Sep 28, 2026, cs.AIJ/K move · Enter open · S save

PILLAR: Private Inverted-Index Lexical Lookup for Augmented Retrieval

Truong Son Nguyen, Daniel Blackley, Ni Trieu, Evgenios M. Kornaropoulos

Arizona State University · Department of Computer Science Arizona State University Tempe, AZ 85281, USA · George Mason University+1

Privacy-Preserving Machine Learning

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Retrieval-augmented generation (RAG) hands the user's query to whoever hosts the corpus. We propose PILLAR, a Privacy-Preserving RAG (PPRAG) system based on Private Information Retrieval (PIR) in which a client utilizes the k documents most similar to their query from a server-held and publicly known corpus to respond to their query, while the server learns nothing about the query, either its terms or its access pattern. Prior PPRAG constructions rely on dense retrieval alone, translating approximate nearest-neighbor search into many query-dependent rounds of PIR, and pay for it in both latency and retrieval quality. PILLAR instead performs private hybrid retrieval in two stages. A sparse stage issues a small, fixed number of PIR queries against a carefully designed index of precomputed BM25 scores, filtering the corpus down to candidates that share terms with the query without the server ever seeing which terms these are. A dense stage then fetches only those candidates' document embeddings and re-ranks them locally, avoiding the many costly PIR queries that private dense retrieval typically requires. We instantiate PILLAR with two protocols that trade latency against retrieval quality, each built on a different private rendering of lexical search. PILLAR-Bin bins posting lists into a hash table and is a single-round design that achieves lower latency than state-of-the-art private retrieval schemes. PILLAR-Tree turns block-max pruning into an oblivious tree traversal combined with cuckoo hash tables and achieves the highest retrieval quality at lower latency than state-of-the-art schemes.

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