Jaggi, Martin
- Advances and Open Problems in Federated Learning
2019/12/10 by Kairouz, Peter, McMahan, H. Brendan, Avent, Brendan +56 · 218 citations
#Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Landmark Attention: Random-Access Infinite Context Length for Transformers
2023/05/25 by Amirkeivan Mohtashami, Mohtashami, Amirkeivan, Martin Jaggi +1 · 2 voices · 16 citations
Computer Science · #Topic Modeling #Advanced Neural Network Applications #Machine Learning and Data Classification
- Evaluating the Search Phase of Neural Architecture Search
2019/02/21 by Kaicheng Yu, Christian Sciuto, Yu, Kaicheng +7 · 2 voices · 3 citations
#cs.LG #stat.ML
- DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging
2024/02/04 by Matteo Pagliardini, Amirkeivan Mohtashami, Pagliardini, Matteo +6 · 1 voice · 13 citations
Computer Science · #Neural Networks and Applications
- QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
2024/03/30 by Saleh Ashkboos, Amirkeivan Mohtashami, Ashkboos, Saleh +14 · 105 citations
Computer Science · Engineering · #Advanced Wireless Communication Techniques #Error Correcting Code Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Optical Network Technologies
- Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks
2023/05/26 by Atli Kosson, Bettina Messmer, Kosson, Atli +3 · 2 voices · 10 citations
Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics
- Sparsified SGD with Memory
2018/09/20 by Sebastian U. Stich, Jean-Baptiste Cordonnier, Stich, Sebastian U. +3 · 47 citations
Computer Science · Engineering · #68W15 #68W40 #90C06 #90C25 #Data Structures and Algorithms (cs.DS) #Distributed #Distributed Sensor Networks and Detection Algorithms #E.4 #F.2.1 #FOS: Computer and information sciences #G.1.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Parallel #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #and Cluster Computing (cs.DC)
- Ensemble Distillation for Robust Model Fusion in Federated Learning
2020/06/12 by Tao Lin, Lin, Tao, Lingjing Kong +5 · 44 citations
Computer Science · Engineering · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Traffic Prediction and Management Techniques
- Error Feedback Fixes SignSGD and other Gradient Compression Schemes
2019/01/28 by Sai Praneeth Karimireddy, Karimireddy, Sai Praneeth, Quentin Rebjock +5 · 33 citations
Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #FOS: Mathematics #I.2.6 #I.5.1 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
- A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
2020/03/23 by Anastasia Koloskova, Koloskova, Anastasia, Nicolas Loizou +7 · 34 citations
Computer Science · #68W10 #68W15 #68W40 #90C06 #90C35 #Cooperative Communication and Network Coding #Distributed #Distributed Control Multi-Agent Systems #F.2.1 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #Stochastic Gradient Optimization Techniques #and Cluster Computing (cs.DC)
- Decentralized Stochastic Optimization and Gossip Algorithms with\n Compressed Communication
2019/02/01 by Anastasia Koloskova, Koloskova, Anastasia, Sebastian U. Stich +3 · 41 citations
Computer Science · #Stochastic Gradient Optimization Techniques #Privacy-Preserving Technologies in Data #Distributed Control Multi-Agent Systems
- FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language
2025/06/26 by Guilherme Penedo, Hynek Kydlíček, Penedo, Guilherme +17 · 1 voice · 33 citations
Computer Science · #Computation and Language (cs.CL) #Educational Technology and Assessment #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Online Learning and Analytics
- MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
2023/11/27 by Zeming Chen, A. Cano, Chen, Zeming +37 · 44 citations
Computer Science · Medicine · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Healthcare and Education #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Healthcare #Topic Modeling
- On the Global Linear Convergence of Frank-Wolfe Optimization Variants
2015/11/18 by Simon Lacoste-Julien, Lacoste-Julien, Simon, Martin Jaggi +1 · 24 citations
Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms
- Model Fusion via Optimal Transport
2019/10/12 by Singh, Sidak Pal, Jaggi, Martin · 18 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations
2024/05/28 by Alexander Hägele, Elie Bakouch, Hägele, Alexander +9 · 33 citations
Decision Sciences · #Scheduling and Timetabling Solutions #Simulation Techniques and Applications
- On the Relationship between Self-Attention and Convolutional Layers
2019/11/08 by Cordonnier, Jean-Baptiste, Loukas, Andreas, Jaggi, Martin · 14 citations
#Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- A Field Guide to Federated Optimization
2021/07/14 by Jianyu Wang, Wang, Jianyu, Zachary Charles +103 · 15 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mobile Crowdsensing and Crowdsourcing #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques
- Don't Use Large Mini-Batches, Use Local SGD
2018/08/22 by Lin, Tao, Stich, Sebastian U., Patel, Kumar Kshitij +1 · 9 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Learning from History for Byzantine Robust Optimization
2020/12/18 by Karimireddy, Sai Praneeth, He, Lie, Jaggi, Martin · 10 citations
#Distributed #FOS: Computer and information sciences #FOS: Mathematics #I.2.6 #I.5.1 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #and Cluster Computing (cs.DC)
- DoGE: Domain Reweighting with Generalization Estimation
2023/10/23 by Simin Fan, Fan, Simin, Matteo Pagliardini +3 · 14 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
- Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning
2022/06/16 by Koloskova, Anastasia, Stich, Sebastian U., Jaggi, Martin · 10 citations
#Distributed #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Parallel #and Cluster Computing (cs.DC)
- FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
2022/10/10 by Jean Ogier du Terrail, Terrail, Jean Ogier du, Samy-Safwan Ayed +45 · 10 citations
Computer Science · Decision Sciences · #Big Data Technologies and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
- Multi-Head Attention: Collaborate Instead of Concatenate
2020/06/29 by Cordonnier, Jean-Baptiste, Loukas, Andreas, Jaggi, Martin · 7 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
2020/06/16 by Sai Praneeth Karimireddy, Karimireddy, Sai Praneeth, Lie He +3 · 7 citations
Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #I.2.6 #I.5.1 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques
- Block-Coordinate Frank-Wolfe Optimization for Structural SVMs
2012/07/19 by Simon Lacoste-Julien, Lacoste-Julien, Simon, Martin Jaggi +5 · 5 citations
Computer Science · Engineering · #68T05 #90C06 #90C52 #90C90 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
2020/08/08 by Karimireddy, Sai Praneeth, Jaggi, Martin, Kale, Satyen +4 · 7 citations
#68W15 #68W40 #90C06 #90C25 #Distributed #E.4 #F.2.1 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #and Cluster Computing (cs.DC)
- CoTFormer: A Chain-of-Thought Driven Architecture with Budget-Adaptive Computation Cost at Inference
2023/10/16 by Mohtashami, Amirkeivan, Pagliardini, Matteo, Jaggi, Martin · 11 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Global linear convergence of Newton's method without strong-convexity or Lipschitz gradients
2018/06/01 by Sai Praneeth Karimireddy, Sebastian U. Stich, Karimireddy, Sai Praneeth +3 · 6 citations
Computer Science · Engineering · Mathematics · #68Q25 #90C25 #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Decentralized Deep Learning with Arbitrary Communication Compression
2019/07/22 by Koloskova, Anastasia, Lin, Tao, Stich, Sebastian U. +1 · 6 citations
#68W10 #68W15 #68W40 #90C06 #90C25 #90C35 #Data Structures and Algorithms (cs.DS) #Distributed #E.4 #F.2.1 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #and Cluster Computing (cs.DC)
- Dynamic Model Pruning with Feedback
2020/06/12 by Lin, Tao, Stich, Sebastian U., Barba, Luis +2 · 6 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Second-order optimization with lazy Hessians
2022/12/01 by Nikita Doikov, El Mahdi Chayti, Doikov, Nikita +3 · 8 citations
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- CoCoA: A General Framework for Communication-Efficient Distributed Optimization
2016/11/07 by Virginia Smith, Simone Forte, Smith, Virginia +9 · 5 citations
Computer Science · #Complexity and Algorithms in Graphs #FOS: Computer and information sciences #Machine Learning (cs.LG) #Optimization and Search Problems #Stochastic Gradient Optimization Techniques
- Agree to Disagree: Diversity through Disagreement for Better Transferability
2022/02/09 by Pagliardini, Matteo, Jaggi, Martin, Fleuret, François +1 · 5 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Masking as an Efficient Alternative to Finetuning for Pretrained Language Models
2020/04/26 by Mengjie Zhao, Zhao, Mengjie, Tao Lin +7 · 4 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling
- A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe
2017/02/21 by Locatello, Francesco, Khanna, Rajiv, Tschannen, Michael +1 · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- COLA: Decentralized Linear Learning
2018/08/13 by He, Lie, Bian, An, Jaggi, Martin · 3 citations
#Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Parallel #and Cluster Computing (cs.DC)
- Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods
2023/02/23 by Chayti, El Mahdi, Doikov, Nikita, Jaggi, Martin · 6 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
- Byzantine-Robust Decentralized Learning via ClippedGossip
2022/02/03 by Lie He, Sai Praneeth Karimireddy, He, Lie +3 · 4 citations
Computer Science · Engineering · #Distributed #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques #Wireless Communication Security Techniques #and Cluster Computing (cs.DC)
- Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains
2024/02/06 by Makkuva, Ashok Vardhan, Bondaschi, Marco, Girish, Adway +4 · 6 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Beyond spectral gap: The role of the topology in decentralized learning
2022/06/07 by Vogels, Thijs, Hendrikx, Hadrien, Jaggi, Martin · 4 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
- Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
2024/02/07 by Doikov, Nikita, Stich, Sebastian U., Jaggi, Martin · 5 citations
#FOS: Mathematics #Optimization and Control (math.OC)
- Efficient Greedy Coordinate Descent for Composite Problems
2018/10/16 by Sai Praneeth Karimireddy, Karimireddy, Sai Praneeth, Anastasia Koloskova +5 · 4 citations
Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Optimization and Search Problems
- Training DNNs with Hybrid Block Floating Point
2018/04/04 by Mario Drumond, Drumond, Mario, Tao Lin +5 · 2 citations
Computer Science · Engineering · #Advanced Data Storage Technologies #FOS: Computer and information sciences #FOS: Mathematics #Ferroelectric and Negative Capacitance Devices #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Parallel Computing and Optimization Techniques
- Safe Adaptive Importance Sampling
2017/11/07 by Stich, Sebastian U., Raj, Anant, Jaggi, Martin · 2 citations
#68Q25 #68W20 #90C25 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #Machine Learning (cs.LG) #Optimization and Control (math.OC)
- Effective Interplay between Sparsity and Quantization: From Theory to Practice
2024/05/31 by Simla Burcu Harma, Harma, Simla Burcu, Ayan Chakraborty +19 · 5 citations
Computer Science · Engineering · #Neural Networks and Applications #Advanced MEMS and NEMS Technologies
- Simple Unsupervised Keyphrase Extraction using Sentence Embeddings
2018/01/13 by Kamil Bennani-Smires, Claudiu Musat, Bennani-Smires, Kamil +7 · 2 citations
Computer Science · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences
- Benchmarking Optimizers for Large Language Model Pretraining
2025/09/01 by Andrei Semenov, A L Semenov, Matteo Pagliardini +4 · 2 voices · 15 citations
Computer Science · Social Sciences · #Computational and Text Analysis Methods #Machine Learning and Data Classification #Topic Modeling #cs.LG
- Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs
2025/04/08 by Dongyang Fan, Fan, Dongyang, Vinko Sabolčec +11 · 3 voices · 2 citations
Computer Science · Decision Sciences · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Research Data Management Practices #Scientific Computing and Data Management #Software Engineering Research
- Secure Byzantine-Robust Machine Learning
2020/06/08 by He, Lie, Karimireddy, Sai Praneeth, Jaggi, Martin · 2 citations
#Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- On Convergence of Incremental Gradient for Non-Convex Smooth Functions
2023/05/30 by Anastasia Koloskova, Nikita Doikov, Koloskova, Anastasia +5 · 3 citations
Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Advanced Neural Network Applications
- Analyzing & Reducing the Need for Learning Rate Warmup in GPT Training
2024/10/31 by Kosson, Atli, Messmer, Bettina, Jaggi, Martin · 7 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
2020/11/03 by Kovalev, Dmitry, Koloskova, Anastasia, Jaggi, Martin +2 · 2 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
- Enhancing Multilingual LLM Pretraining with Model-Based Data Selection
2025/02/14 by Bettina Messmer, Vinko Sabolčec, Messmer, Bettina +3 · 6 citations
Computer Science · #Natural Language Processing Techniques #Text Readability and Simplification
- Masked Training of Neural Networks with Partial Gradients
2021/06/16 by Amirkeivan Mohtashami, Martin Jaggi, Mohtashami, Amirkeivan +3 · 2 citations
Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Stochastic Gradient Optimization Techniques
- MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks
2023/09/25 by Vinitra Swamy, Malika Satayeva, Swamy, Vinitra +13 · 3 citations
Computer Science · Medicine · #Machine Learning in Healthcare #COVID-19 diagnosis using AI #Explainable Artificial Intelligence (XAI)
- Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
2021/02/09 by Lin, Tao, Karimireddy, Sai Praneeth, Stich, Sebastian U. +1 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Special Properties of Gradient Descent with Large Learning Rates
2022/05/30 by Amirkeivan Mohtashami, Martin Jaggi, Mohtashami, Amirkeivan +3 · 2 citations
Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and ELM #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
- The Privacy Power of Correlated Noise in Decentralized Learning
2024/05/02 by Youssef Allouah, Allouah, Youssef, Anastasia Koloskova +7 · 3 citations
Computer Science · #Cryptography and Security (cs.CR) #Distributed #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #Privacy-Preserving Technologies in Data #and Cluster Computing (cs.DC)
- Communication-Efficient Distributed Dual Coordinate Ascent
2014/09/04 by Jaggi, Martin, Smith, Virginia, Takáč, Martin +4 · 1 citation
#68W15 #90C25 #C.1.4 #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
- Collaborative Learning via Prediction Consensus
2023/05/29 by Fan, Dongyang, Mendler-Dünner, Celestine, Jaggi, Martin · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Generating Steganographic Text with LSTMs
2017/05/30 by Fang, Tina, Jaggi, Martin, Argyraki, Katerina · 1 citation
#Artificial Intelligence (cs.AI) #Cryptography and Security (cs.CR) #E.3 #FOS: Computer and information sciences #I.2.7 #Multimedia (cs.MM)
- Towards an empirical understanding of MoE design choices
2024/02/20 by Dongyang Fan, Fan, Dongyang, Bettina Messmer +3 · 2 citations
Business, Management and Accounting · Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Innovative Approaches in Technology and Social Development #Machine Learning (cs.LG) #Technology Use by Older Adults #Usability and User Interface Design
- Improving Stochastic Cubic Newton with Momentum
2024/10/25 by Chayti, El Mahdi, Doikov, Nikita, Jaggi, Martin · 4 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
- Extrapolation for Large-batch Training in Deep Learning
2020/06/10 by Tao Lin, Lingjing Kong, Lin, Tao +5 · 1 citation
Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #Adversarial Robustness in Machine Learning
- Layer-wise Linear Mode Connectivity
2023/07/13 by Linara Adilova, Adilova, Linara, Andriushchenko, Maksym +3 · 2 citations
Engineering · #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #Machine Learning (cs.LG) #Optical Wireless Communication Technologies #Semiconductor Lasers and Optical Devices
- Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates
2021/03/03 by Stich, Sebastian U., Mohtashami, Amirkeivan, Jaggi, Martin · 1 citation
#Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Parallel #and Cluster Computing (cs.DC)
- Implicit Gradient Alignment in Distributed and Federated Learning
2021/06/25 by Dandi, Yatin, Barba, Luis, Jaggi, Martin · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Deep Grokking: Would Deep Neural Networks Generalize Better?
2024/05/29 by Fan, Simin, Pascanu, Razvan, Jaggi, Martin · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Obtaining Better Static Word Embeddings Using Contextual Embedding Models
2021/06/08 by Prakhar Gupta, Martin Jaggi, Gupta, Prakhar +1 · 1 citation
Computer Science · #Natural Language Processing Techniques #Topic Modeling #Text Readability and Simplification
- Towards Fully FP8 GEMM LLM Training at Scale
2025/05/26 by Hernández-Cano, Alejandro, Garbaya, Dhia, Schlag, Imanol +1 · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists
2024/09/20 by Dongyang Fan, Fan, Dongyang, Bettina Messmer +3 · 2 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Speech and dialogue systems
- Optimal Model Averaging: Towards Personalized Collaborative Learning
2021/10/25 by Felix Grimberg, Mary‐Anne Hartley, Grimberg, Felix +5 · 1 citation
Computer Science · Mathematics · #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques #Statistical Methods and Inference
- Linear Speedup in Personalized Collaborative Learning
2021/11/10 by Chayti, El Mahdi, Karimireddy, Sai Praneeth, Stich, Sebastian U. +2 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Interpreting Language Models Through Knowledge Graph Extraction
2021/11/16 by Swamy, Vinitra, Romanou, Angelika, Jaggi, Martin · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Data-heterogeneity-aware Mixing for Decentralized Learning
2022/04/13 by Dandi, Yatin, Koloskova, Anastasia, Jaggi, Martin +1 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
- Characterizing & Finding Good Data Orderings for Fast Convergence of Sequential Gradient Methods
2022/02/03 by Mohtashami, Amirkeivan, Stich, Sebastian, Jaggi, Martin · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Modular Clinical Decision Support Networks (MoDN) -- Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments
2022/11/12 by Trottet, Cécile, Vogels, Thijs, Jaggi, Martin +1 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Beyond spectral gap (extended): The role of the topology in decentralized learning
2023/01/05 by Thijs Vogels, Vogels, Thijs, Hadrien Hendrikx +3 · 1 citation
Computer Science · #Age of Information Optimization #Distributed #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Parallel #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques #and Cluster Computing (cs.DC)
- HyperINF: Unleashing the HyperPower of the Schulz's Method for Data Influence Estimation
2024/10/07 by Zhou, Xinyu, Fan, Simin, Jaggi, Martin · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Multiplication-Free Transformer Training via Piecewise Affine Operations
2023/05/26 by Atli Kosson, Kosson, Atli, Martin Jaggi +1 · 1 citation
Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
- LASER: Linear Compression in Wireless Distributed Optimization
2023/10/19 by Ashok Vardhan Makkuva, Makkuva, Ashok Vardhan, Marco Bondaschi +8 · 1 citation
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Leveraging the true depth of LLMs
2025/02/05 by Ramón Calvo González, González, Ramón Calvo, Daniele Paliotta +7 · 2 voices · 1 citation
#cs.LG #cs.CL
- Intrinsic User-Centric Interpretability through Global Mixture of Experts
2024/02/05 by Swamy, Vinitra, Montariol, Syrielle, Blackwell, Julian +3 · 1 citation
#Computers and Society (cs.CY) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG)
- GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining
2025/05/26 by Simin Fan, Fan, Simin, Maria Ios Glarou +3 · 2 citations
Engineering · #Advanced Measurement and Detection Methods #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
2025/09/17 by Apertus, Project, Hernández-Cano, Alejandro, Hägele, Alexander +100 · 9 citations
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs
2025/02/07 by Bossy, Thierry, Vignoud, Julien, Rabbani, Tahseen +2 · 1 citation
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- CoBo: Collaborative Learning via Bilevel Optimization
2024/09/09 by Diba Hashemi, Lie He, Hashemi, Diba +3 · 1 citation
Psychology · #Distributed #FOS: Computer and information sciences #Innovative Teaching and Learning Methods #Machine Learning (cs.LG) #Parallel #and Cluster Computing (cs.DC)
- Greedy Algorithms for Cone Constrained Optimization with Convergence\n Guarantees
2017/05/31 by Francesco Locatello, Michael Tschannen, Locatello, Francesco +5 · 1 citation
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques