Yu, Bin
- LoRA+: Efficient Low Rank Adaptation of Large Models
2024/02/19 by Soufiane Hayou, N. C. Ghosh, Nikhil Ghosh +4 · 3 voices · 67 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Speech Recognition and Synthesis
- High-dimensional covariance estimation by minimizing ℓ1-penalized log-determinant divergence
2008/11/21 by Pradeep Ravikumar, Ravikumar, Pradeep, Martin J. Wainwright +5 · 10 citations
Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #Statistical Methods and Inference #Statistical Mechanics and Entropy
- Statistical guarantees for the EM algorithm: From population to sample-based analysis
2014/08/09 by Balakrishnan, Sivaraman, Wainwright, Martin J., Yu, Bin · 10 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Minimax rates of estimation for high-dimensional linear regression over ℓq-balls
2009/10/11 by Garvesh Raskutti, Martin J. Wainwright, Raskutti, Garvesh +3 · 6 citations
Engineering · Decision Sciences · Mathematics · #Sparse and Compressive Sensing Techniques #Probabilistic and Robust Engineering Design #Statistical Methods and Inference
- A Statistical Perspective on Algorithmic Leveraging
2013/06/23 by Ping Ma, Ma, Ping, Michael W. Mahoney +3 · 8 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistical Methods and Inference
- Early stopping and non-parametric regression: An optimal data-dependent stopping rule
2013/06/15 by Raskutti, Garvesh, Wainwright, Martin J., Yu, Bin · 6 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
2019/09/30 by Laura Rieger, Chandan Singh, Rieger, Laura +5 · 10 citations
Computer Science · #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
- SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference
2023/07/05 by Del Corro, Luciano, Del Giorno, Allie, Agarwal, Sahaj +3 · 10 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
2023/11/03 by Qingru Zhang, Chandan Singh, Zhang, Qingru +11 · 7 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
- Artificial Intelligence and Statistics
2017/12/08 by Bin Yu, Yu, Bin, Karl Kumbier +1 · 4 citations
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Data Analysis with R #FOS: Computer and information sciences #Forecasting Techniques and Applications #Machine Learning (stat.ML) #Statistical and Computational Modeling
- Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning
2024/01/25 by Yanda Chen, Chen, Yanda, Chandan Singh +11 · 8 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling
- Singularity, Misspecification, and the Convergence Rate of EM
2018/10/01 by Raaz Dwivedi, Dwivedi, Raaz, Nhat Ho +9 · 5 citations
Computer Science · Mathematics · #62G05 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Primary 62F15 #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST) #secondary 62G20
- The Impact of Initialization on LoRA Finetuning Dynamics
2024/06/12 by Soufiane Hayou, N. C. Ghosh, Hayou, Soufiane +3 · 8 citations
Engineering · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Vibration and Dynamic Analysis
- Adaptive wavelet distillation from neural networks through interpretations
2021/07/19 by Woo‐Seok Ha, Ha, Wooseok, Chandan Singh +8 · 4 citations
Computer Science · Materials Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science
- Bridging Discrete and Backpropagation: Straight-Through and Beyond
2023/04/17 by Liyuan Liu, Chengyu Dong, Liu, Liyuan +7 · 5 citations
Computer Science · Physics and Astronomy · #Machine Learning and Data Classification #Neural Networks and Applications #Model Reduction and Neural Networks
- Minimax-optimal rates for sparse additive models over kernel classes via convex programming
2010/08/21 by Garvesh Raskutti, Martin J. Wainwright, Raskutti, Garvesh +3 · 3 citations
Mathematics · Computer Science · Engineering · #Statistical Methods and Inference #Machine Learning and Algorithms #Control Systems and Identification
- Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models
2019/02/01 by Raaz Dwivedi, Nhat Ho, Dwivedi, Raaz +9 · 3 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST)
- TrafficGPT: Viewing, Processing and Interacting with Traffic Foundation Models
2023/09/13 by Siyao Zhang, Daocheng Fu, Zhang, Siyao +7 · 5 citations
Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Traffic Prediction and Management Techniques
- Complexity Analysis of the Lasso Regularization Path
2012/05/01 by Mairal, Julien, Yu, Bin · 2 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
- Estimation Stability with Cross Validation (ESCV)
2013/03/13 by Lim, Chinghway, Yu, Bin · 2 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
- Minimum-Norm Interpolation Under Covariate Shift
2024/03/31 by Neil Mallinar, Austin Zane, Mallinar, Neil +5 · 5 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Speech Recognition and Synthesis
- Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
2018/01/16 by Murdoch, W. James, Liu, Peter J., Yu, Bin · 2 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Stability and Convergence Trade-off of Iterative Optimization Algorithms
2018/04/04 by Chen, Yuansi, Jin, Chi, Yu, Bin · 2 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition
2024/07/01 by Aliyah R. Hsu, Hsu, Aliyah R., Zhou, Georgia +9 · 5 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Machine Learning (cs.LG)
- Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients
2019/05/29 by Chen, Yuansi, Dwivedi, Raaz, Wainwright, Martin J. +1 · 2 citations
#Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Incremental causal effects
2019/07/30 by Rothenhäusler, Dominik, Yu, Bin · 2 citations
#FOS: Computer and information sciences #Methodology (stat.ME)
- Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency
2024/02/24 by Wu, Jingfeng, Bartlett, Peter L., Telgarsky, Matus +1 · 4 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Explaining black box text modules in natural language with language models
2023/05/17 by Singh, Chandan, Hsu, Aliyah R., Antonello, Richard +4 · 3 citations
#Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neurons and Cognition (q-bio.NC)
- Long-Short Chain-of-Thought Mixture Supervised Fine-Tuning Eliciting Efficient Reasoning in Large Language Models
2025/05/06 by Bin Yu, Hang Yuan, Yu, Bin +13 · 10 citations
Computer Science · #Topic Modeling #Natural Language Processing Techniques
- Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods
2022/02/02 by Abhineet Agarwal, Yan Shuo Tan, Agarwal, Abhineet +7 · 2 citations
Computer Science · Environmental Science · #Applications (stat.AP) #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Hydrological Forecasting Using AI #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Methodology (stat.ME)
- A path following algorithm for Sparse Pseudo-Likelihood Inverse Covariance Estimation (SPLICE)
2008/07/23 by Guilherme V. Rocha, Peng Zhao, Rocha, Guilherme V. +3 · 1 citation
Engineering · #Computation (stat.CO) #FOS: Computer and information sciences #Fault Detection and Control Systems #Methodology (stat.ME) #Sparse and Compressive Sensing Techniques #Structural Health Monitoring Techniques
- KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data
2024/10/10 by Andy Zhou, Xiaojun Xu, Zhou, Andy +10 · 4 citations
Computer Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Semantic Web and Ontologies
- Asymptotic Properties of Lasso+mLS and Lasso+Ridge in Sparse High-dimensional Linear Regression
2013/06/24 by Liu, Hanzhong, Yu, Bin · 1 citation
#FOS: Mathematics #Statistics Theory (math.ST)
- Error Rate Bounds and Iterative Weighted Majority Voting for Crowdsourcing
2014/11/15 by Li, Hongwei, Yu, Bin · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR) #Statistics Theory (math.ST)
- Superheat: An R package for creating beautiful and extendable heatmaps for visualizing complex data
2015/12/04 by Rebecca Barter, Bin Yu, Barter, Rebecca L +1 · 1 citation
Computer Science · #Applications (stat.AP) #Data Analysis with R #FOS: Computer and information sciences #Methodology (stat.ME)
- Interpreting Convolutional Neural Networks Through Compression
2017/11/07 by Abbasi-Asl, Reza, Yu, Bin · 1 citation
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- High-speed Tracking with Multi-kernel Correlation Filters
2018/06/17 by Ming Tang, Tang, Ming, Bin Yu +5 · 1 citation
Computer Science · Engineering · Earth and Planetary Sciences · #Video Surveillance and Tracking Methods #Gait Recognition and Analysis #Remote Sensing and Land Use
- Designing a Data Science simulation with MERITS: A Primer
2024/03/13 by Elliott, Corrine F, Duncan, James PC, Tang, Tiffany M +3 · 2 citations
#Computation (stat.CO) #FOS: Computer and information sciences
- Revisiting minimum description length complexity in overparameterized models
2020/06/17 by Raaz Dwivedi, Chandan Singh, Dwivedi, Raaz +5 · 1 citation
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Statistical Methods and Inference #Statistics Theory (math.ST)
- Not All Tokens Are What You Need In Thinking
2025/05/23 by Yuan, Hang, Yu, Bin, Li, Haotian +6 · 5 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- Signed iterative random forests to identify enhancer-associated transcription factor binding
2018/10/16 by Karl Kumbier, Sumanta Basu, Kumbier, Karl +9 · 1 citation
Biochemistry, Genetics and Molecular Biology · #FOS: Computer and information sciences #Genomics and Chromatin Dynamics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #RNA Research and Splicing #RNA and protein synthesis mechanisms
- Fast Interpretable Greedy-Tree Sums
2022/01/28 by Yan Shuo Tan, Chandan Singh, Tan, Yan Shuo +10 · 1 citation
Computer Science · Health Professions · #Explainable Artificial Intelligence (XAI) #Machine Learning in Healthcare #Artificial Intelligence in Healthcare
- Same Root Different Leaves: Time Series and Cross-Sectional Methods in Panel Data
2022/07/29 by Shen, Dennis, Ding, Peng, Sekhon, Jasjeet +1 · 1 citation
#Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Methodology (stat.ME)
- Generative causal testing to bridge data-driven models and scientific theories in language neuroscience
2024/10/01 by Richard Antonello, Chandan Singh, Antonello, Richard +12 · 2 citations
Computer Science · Social Sciences · #Computation and Language (cs.CL) #FOS: Biological sciences #FOS: Computer and information sciences #Language and cultural evolution #Natural Language Processing Techniques #Neurons and Cognition (q-bio.NC) #Topic Modeling
- The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning
2023/08/06 by Nikhil Ghosh, Ghosh, Nikhil, Spencer Frei +5 · 1 citation
Computer Science · Physics and Astronomy · #Stochastic Gradient Optimization Techniques #Model Reduction and Neural Networks #Machine Learning and ELM
- Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
2025/02/18 by Wu, Jingfeng, Bartlett, Peter, Telgarsky, Matus +1 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation
2023/09/26 by Li, Haotian, Yu, Bin, Wei, Yuliang +3 · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences
- Optimal Subsampling Approaches for Large Sample Linear Regression
2015/09/17 by Rong Zhu, Ping Ma, Zhu, Rong +5 · 1 citation
Computer Science · Engineering · #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework
2025/05/13 by Abhineet Agarwal, Fange Xiao, Agarwal, Abhineet +9 · 3 citations
#stat.ML #cs.LG #math.ST #stat.ME #stat.TH
- A Signature Based Approach Towards Global Channel Charting with Ultra Low Complexity
2024/03/29 by Longhai Zhao, Yunchuan Yang, Zhao, Longhai +11 · 1 citation
Engineering · #Advanced Wireless Communication Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Power Line Communications and Noise #Signal Processing (eess.SP) #electronic engineering #information engineering
- Classifying expanding attractors on figure eight knot complement space and non-transitive Anosov flows on Franks-Williams manifold
2020/04/19 by Yang, Jiagang, Yu, Bin · 1 citation
#Dynamical Systems (math.DS) #FOS: Mathematics #Geometric Topology (math.GT)
- PCS Workflow for Veridical Data Science in the Age of AI
2025/06/18 by Rewolinski, Zachary T., Yu, Bin · 3 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Methodology (stat.ME)
- The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis
2024/06/28 by Tan, Yan Shuo, Ronen, Omer, Saarinen, Theo +1 · 1 citation
#62G08 #65C40 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- On mixing enhancement by secondary baroclinic vorticity in shock-bubble interaction
2020/07/11 by Sen-Hui Liu, Liu, Hong, Bin Yu +5 · 1 citation
Engineering · Mathematics · #Computational Fluid Dynamics and Aerodynamics #Fluid Dynamics and Turbulent Flows #Gas Dynamics and Kinetic Theory
- Ultralow-pressure mechanical-motion switching of ferroelectric polarization
2025/03/25 by Wang, Baoyu, He, Xin, Luo, Jianjun +20 · 1 citation
#FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Mesoscale and Nanoscale Physics (cond-mat.mes-hall)