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Thorpe, Matthew

  1. Analysis of p-Laplacian Regularization in Semi-Supervised Learning
    2017/07/19 by Slepčev, Dejan, Thorpe, Matthew · 6 citations
    #35J20 #49J45 #49J55 #62G20 #65N12 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
  2. Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label\n Rates
    2020/06/19 by Jeff Calder, Brendan Cook, Calder, Jeff +5 · 6 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
  3. Deep Limits of Residual Neural Networks
    2018/10/28 by Thorpe, Matthew, van Gennip, Yves · 4 citations
    #34E05 #39A30 #39A60 #49J15 #49J45 #Classical Analysis and ODEs (math.CA) #FOS: Mathematics
  4. The Linearized Hellinger--Kantorovich Distance
    2021/02/17 by Cai, Tianji, Cheng, Junyi, Schmitzer, Bernhard +1 · 4 citations
    #FOS: Mathematics #Optimization and Control (math.OC)
  5. Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning\n Algorithms
    2018/05/23 by Matthew M. Dunlop, Dunlop, Matthew M., Dejan Slepčev +5 · 3 citations
    Decision Sciences · Engineering · Mathematics · #49J55 #62C10 #62F15 #62G20 #Advanced Bandit Algorithms Research #Advanced Optimization Algorithms Research #Analysis of PDEs (math.AP) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques
  6. Convergence of the k-Means Minimization Problem using Γ-Convergence
    2015/01/06 by Thorpe, Matthew, Theil, Florian, Johansen, Adam M. +1 · 2 citations
    #FOS: Mathematics #Functional Analysis (math.FA) #Optimization and Control (math.OC) #Statistics Theory (math.ST)
  7. Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates
    2020/06/04 by Jeff Calder, Dejan Slepčev, Calder, Jeff +3 · 3 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
  8. A Transportation Lp Distance for Signal Analysis
    2016/09/27 by Matthew Thorpe, Thorpe, Matthew, Serim Park +7 · 2 citations
    Computer Science · #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods #Medical Image Segmentation Techniques
  9. Expected Sliced Transport Plans
    2024/10/16 by Xinran Liu, Liu, Xinran, Rocío Díaz Martín +11 · 5 citations
    Business, Management and Accounting · Engineering · #Advanced Manufacturing and Logistics Optimization #FOS: Computer and information sciences #FOS: Mathematics #Law, logistics, and international trade #Machine Learning (cs.LG) #Metric Geometry (math.MG)
  10. Manifold learning in Wasserstein space
    2023/11/14 by Keaton Hamm, Caroline Moosmüller, Hamm, Keaton +5 · 2 citations
    Computer Science · #41A65 #49Q22 #53Z50 #58B20 #Differential Geometry (math.DG) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Topological and Geometric Data Analysis
  11. Asymptotic analysis of the Ginzburg–Landau functional on point clouds
    2016/04/17 by Matthew Thorpe, Florian Theil, Thorpe, Matthew +1 · 1 citation
    Computer Science · Mathematics · #Advanced Mathematical Modeling in Engineering #Analysis of PDEs (math.AP) #FOS: Mathematics #Geometric Analysis and Curvature Flows #Topological and Geometric Data Analysis
  12. Large data limit for a phase transition model with the p-Laplacian on point clouds
    2018/02/23 by Riccardo Cristoferi, Cristoferi, Riccardo, Matthew Thorpe +1 · 1 citation
    Computer Science · Mathematics · #Analysis of PDEs (math.AP) #FOS: Mathematics #Geometric Analysis and Curvature Flows #Stochastic processes and statistical mechanics #Topological and Geometric Data Analysis
  13. Consistency of Fractional Graph-Laplacian Regularization in Semi-Supervised Learning with Finite Labels
    2023/03/14 by Adrien Weihs, Weihs, Adrien, Matthew Thorpe +1 · 2 citations
    Biochemistry, Genetics and Molecular Biology · Mathematics · #Circular RNAs in diseases #FOS: Mathematics #Mathematical Approximation and Integration #MicroRNA in disease regulation #Statistics Theory (math.ST)
  14. From graph cuts to isoperimetric inequalities: Convergence rates of Cheeger cuts on data clouds
    2020/04/20 by Nicolás García Trillos, Ryan Murray, Trillos, Nicolas Garcia +3 · 1 citation
    Computer Science · Engineering · Mathematics · #Topological and Geometric Data Analysis #3D Shape Modeling and Analysis #Point processes and geometric inequalities
  15. PTLp: Partial Transport Lp Distances
    2023/07/25 by Liu, Xinran, Bai, Yikun, Tran, Huy +3 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  16. Rates of Convergence for Regression with the Graph Poly-Laplacian
    2022/09/06 by Trillos, Nicolás García, Murray, Ryan, Thorpe, Matthew · 1 citation
    #Analysis of PDEs (math.AP) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Γ-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation
    2022/02/10 by Irene Fonseca, Lisa Maria Kreußer, Fonseca, Irene +5 · 1 citation
    Engineering · Mathematics · #Analysis of PDEs (math.AP) #FOS: Mathematics #Mathematical Approximation and Integration #Numerical Analysis (math.NA) #Numerical methods in inverse problems #Optimization and Control (math.OC) #Thermoelastic and Magnetoelastic Phenomena
  18. Transport-based analysis, modeling, and learning from signal and data\n distributions
    2016/09/15 by Soheil Kolouri, Kolouri, Soheil, Serim Park +7 · 3 citations
    Chemistry · Computer Science · Environmental Science · #AI in cancer detection #Bayesian Methods and Mixture Models #Computer Vision and Pattern Recognition (cs.CV) #Electrostatics and Colloid Interactions #FOS: Computer and information sciences #Hydrological Forecasting Using AI #Image Retrieval and Classification Techniques #Medical Image Segmentation Techniques