Jeff Calder

1. Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label\n Rates
   2020/06/19 by Jeff Calder, Brendan Cook, Calder, Jeff +5 · 5 citations
   Computer Science · #05C81 #35J08 #35J15 #35R02 #68T05 #Analysis of PDEs (math.AP) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #G.1.8 #G.2.2 #I.2.6 #I.4.0 #I.5.3 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Multimodal Machine Learning Applications #Numerical Analysis (math.NA) #Text and Document Classification Technologies
2. Consistency of Lipschitz learning with infinite unlabeled data and\n finite labeled data
   2017/10/27 by Jeff Calder, Calder, Jeff · 3 citations
   Computer Science · Mathematics · #35D40 #35J60 #65N06 #Analysis of PDEs (math.AP) #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Statistical Methods and Inference
3. Improved spectral convergence rates for graph Laplacians on ε-graphs and k-NN graphs
   2022/03/04 by Jeff Calder, Nicolás García Trillos · 3 citations
   Computer Science · Mathematics · #Advanced Mathematical Modeling in Engineering #Graph theory and applications #Spectral Theory in Mathematical Physics
4. Analysis and algorithms for ℓ_p-based semi-supervised learning on graphs
   2019/01/15 by Mauricio A. Flores, Flores, Mauricio, Jeff Calder +3 · 2 citations
   Computer Science · Engineering · Mathematics · #35D40 #35R02 #65N06 #68T05 #68W01 #Analysis of PDEs (math.AP) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference
5. Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates
   2020/06/04 by Jeff Calder, Calder, Jeff, Dejan Slepčev +3 · 2 citations
   Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
6. Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth
   2022/02/17 by Jeff Calder, Mahmood Ettehad, Calder, Jeff +1 · 2 citations
   Computer Science · #Topological and Geometric Data Analysis #Anomaly Detection Techniques and Applications
7. Boundary Estimation from Point Clouds: Algorithms, Guarantees and\n Applications
   2021/11/04 by Jeff Calder, Sangmin Park, Calder, Jeff +3 · 1 citation
   Mathematics · #62G20 #65D99 #65N12 #65N15 #65N75 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Numerical methods in inverse problems #Statistical Methods and Inference #Statistics Theory (math.ST)
8. Graph-based Active Learning for Semi-supervised Classification of SAR Data
   2022/03/31 by Kevin Miller, John C. Mauro, Miller, Kevin +11 · 1 citation
   Computer Science · Engineering · #Machine Learning and Algorithms #Domain Adaptation and Few-Shot Learning #Advanced SAR Imaging Techniques
9. Geometry-Preserving Encoder/Decoder in Latent Generative Models
   2025/01/16 by Wonjun Lee, Riley C. W. O'Neill, Lee, Wonjun +7 · 1 citation
   Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Semantic Web and Ontologies