Daniel Reichman

Most-cited papers

1. Using large-scale experiments and machine learning to discover theories of human decision-making

   Joshua C. Peterson, David D. Bourgin, Mayank Agrawal, Daniel Reichman +1 more

   2021Science250 citations

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2. Earth Beings: Ecologies of Practice across Andean Worlds

   M. de la Cadena, R. J. Foster, Daniel Reichman

   2015244 citations

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3. Fast-Match: Fast Affine Template Matching

   Simon Korman, Daniel Reichman, Gilad Tsur, S. Avidan

   2013International Journal of Computer Vision219 citations

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4. On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank One Perturbations of Gaussian Tensors

   A. Montanari, Daniel Reichman, O. Zeitouni

   2014IEEE Transactions on Information Theory102 citations Open access

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5. Cognitive Model Priors for Predicting Human Decisions

   David D. Bourgin, Joshua C. Peterson, Daniel Reichman, T. Griffiths +1 more

   2019International Conference on Machine Learning94 citations

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6. Tiling and Stitching Segmentation Output for Remote Sensing: Basic Challenges and Recommendations

   Bohao Huang, Daniel Reichman, L. Collins, Kyle Bradbury +1 more

   201860 citations

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7. Contagious Sets in Expanders

   Amin Coja-Oghlan, U. Feige, Michael Krivelevich, Daniel Reichman

   2013ACM-SIAM Symposium on Discrete Algorithms59 citations

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8. Tight Hardness Results for Training Depth-2 ReLU Networks

   Surbhi Goel, Adam R. Klivans, Pasin Manurangsi, Daniel Reichman

   2020Information Technology Convergence and Services54 citations

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9. Predicting human decisions with behavioral theories and machine learning

   Ori Plonsky, Reut Apel, E. Ert, Moshe Tennenholtz +8 more

   2019arXiv.org53 citations

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10. Improving convolutional neural networks for buried target detection in ground penetrating radar using transfer learning via pretraining

    John Bralich, Daniel Reichman, L. Collins, Jordan M. Malof

    2017Defense + Security53 citations

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11. Some good practices for applying convolutional neural networks to buried threat detection in Ground Penetrating Radar

    Daniel Reichman, L. Collins, Jordan M. Malof

    2017International Workshop on Advanced Ground Penetrating Radar51 citations

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12. The Computational Complexity of Training ReLU(s)

    Pasin Manurangsi, Daniel Reichman

    2018arXiv.org47 citations

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13. A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar

    Jordan M. Malof, Daniel Reichman, A. Karem, H. Frigui +5 more

    2018IEEE Transactions on Geoscience and Remote Sensing39 citations Open access

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14. Contagious Sets in Random Graphs

    U. Feige, Michael Krivelevich, Daniel Reichman

    201632 citations Open access

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15. Smoothed Analysis on Connected Graphs

    Michael Krivelevich, Daniel Reichman, Wojciech Samotij

    2013SIAM Journal on Discrete Mathematics29 citations Open access

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16. On the Rational Boundedness of Cognitive Control: Shared Versus Separated Representations

    Sebastian Musslick, Andrew M. Saxe, A. N. Hoskin, Daniel Reichman +1 more

    202028 citations Open access

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17. On Choosing Training and Testing Data for Supervised Algorithms in Ground-Penetrating Radar Data for Buried Threat Detection

    Daniel Reichman, L. Collins, Jordan M. Malof

    2016IEEE Transactions on Geoscience and Remote Sensing28 citations Open access

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18. Contagious sets in dense graphs

    Daniel Freund, Matthias Poloczek, Daniel Reichman

    2015European journal of combinatorics (Print)23 citations Open access

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19. Putting climate-induced migration in context: the case of Honduran migration to the USA

    Daniel Reichman

    2022Regional Environmental Change16 citations Open access

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20. Improvements to the Histogram of Oriented Gradient (HOG) prescreener for buried threat detection in ground penetrating radar data

    Daniel Reichman, L. Collins, Jordan M. Malof

    2017Defense + Security16 citations

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21. Deleting and Testing Forbidden Patterns in Multi-Dimensional Arrays

    Omri Ben-Eliezer, Simon Korman, Daniel Reichman

    2016International Colloquium on Automata, Languages and Programming15 citations

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22. A graph-theoretic approach to multitasking

    N. Alon, Daniel Reichman, Igor Shinkar, Tal Wagner +5 more

    2016Neural Information Processing Systems15 citations

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23. Size and Depth of Monotone Neural Networks: Interpolation and Approximation

    Dan Mikulincer, Daniel Reichman

    2022IEEE Transactions on Neural Networks and Learning Systems14 citations Open access

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24. Big Coffee in Brazil: Historical Origins and Implications for Anthropological Political Economy

    Daniel Reichman

    201814 citations

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25. LP-Based Robust Algorithms for Noisy Minor-Free and Bounded Treewidth Graphs

    N. Bansal, Daniel Reichman, S. Umboh

    2016ACM-SIAM Symposium on Discrete Algorithms14 citations Open access

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26. Target localization and signature extraction in GPR data using expectation-maximization and principal component analysis

    Daniel Reichman, K. Morton, L. Collins, P. Torrione

    2014Defense + Security Symposium14 citations

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27. How Many Neurons Does it Take to Approximate the Maximum?

    Itay Safran, Daniel Reichman, Paul Valiant

    2023ACM-SIAM Symposium on Discrete Algorithms13 citations Open access

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28. How do we choose the best model? The impact of cross-validation design on model evaluation for buried threat detection in ground penetrating radar

    Jordan M. Malof, Daniel Reichman, L. Collins

    2018Defense + Security11 citations

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29. Algorithm development for deeply buried threat detection in GPR data

    Daniel Reichman, Jordan M. Malof, L. Collins

    2016SPIE Defense + Security11 citations

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30. Learning improved pooling regions for the Histogram of Oriented Gradient (HOG) feature for buried threat detection in ground penetrating radar

    Daniel Reichman, L. Collins, Jordan M. Malof

    2017Defense + Security10 citations

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31. Target signature localization in GPR data by jointly estimating and matching templates

    Daniel Reichman, K. Morton, Jordan M. Malof, L. Collins +1 more

    2015Defense + Security Symposium10 citations

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32. Improving the histogram of oriented gradient feature for threat detection in ground penetrating radar by implementing it as a trainable convolutional neural network

    Jordan M. Malof, John Bralich, Daniel Reichman, L. Collins

    2018Defense + Security9 citations

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33. The Structure of Goal Systems Predicts Human Performance

    David D. Bourgin, Falk Lieder, Daniel Reichman, Nimrod Talmon +1 more

    2017Annual Meeting of the Cognitive Science Society9 citations

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34. Inference in Sparse Graphs with Pairwise Measurements and Side Information

    Dylan J. Foster, Daniel Reichman, Karthik Sridharan

    2017International Conference on Artificial Intelligence and Statistics8 citations

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35. Entrepreneurship in a Pickle: Innovation and Arbitrage in the Sea Cucumber Trade

    Daniel Reichman

    20138 citations

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36. Size and Depth Separation in Approximating Natural Functions with Neural Networks

    Gal Vardi, Daniel Reichman, T. Pitassi, Ohad Shamir

    2021Annual Conference Computational Learning Theory7 citations

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37. Reliable training of convolutional neural networks for GPR-based buried threat detection using the Adam optimizer and batch normalization

    S. Jacobson, Daniel Reichman, Joel Bjornstad, L. Collins +1 more

    2019Defense + Commercial Sensing7 citations

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38. On Percolation and NP-Hardness

    Daniel Reichman, Igor Shinkar

    2015Electron. Colloquium Comput. Complex.6 citations

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39. Dense labeling of large remote sensing imagery with convolutional neural networks: a simple and faster alternative to stitching output label maps

    Bohao Huang, Daniel Reichman, L. Collins, Kyle Bradbury +1 more

    2018arXiv.org5 citations

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40. gprHOG and the popularity of Histogram of Oriented Gradients (HOG) for Buried Threat Detection in Ground-Penetrating Radar

    Daniel Reichman, L. Collins, Jordan M. Malof

    20185 citations

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41. Discriminative dictionary learning to learn effective features for detecting buried threats in ground penetrating radar data

    Jordan M. Malof, Daniel Reichman, L. Collins

    2017Defense + Security5 citations

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42. On giant components and treewidth in the layers model

    U. Feige, J. Hermon, Daniel Reichman

    2014Random Struct. Algorithms5 citations Open access

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43. Sharp thresholds and the partition function

    Amin Coja-Oghlan, Daniel Reichman

    20135 citations Open access

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44. gprHOG: Several Simple Improvements to the Histogram of Oriented Gradients Feature for Threat Detection in Ground-Penetrating Radar

    Daniel Reichman, L. Collins, Jordan M. Malof

    2018arXiv.org4 citations

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45. String Matching: Communication, Circuits, and Learning

    Alexander Golovnev, Mika Göös, Daniel Reichman, Igor Shinkar

    2017International Workshop and International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques4 citations

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46. The effect of translational variance in training and testing images on supervised buried threat detection algorithms for ground penetrating radar

    Daniel Reichman, L. Collins, Jordan M. Malof

    2017International Workshop on Advanced Ground Penetrating Radar4 citations

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47. Multitasking Capacity: Hardness Results and Improved Constructions

    N. Alon, J. Cohen, T. Griffiths, Pasin Manurangsi +4 more

    2018SIAM Journal on Discrete Mathematics3 citations Open access

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48. The Computational Challenges of Means Selection Problems: Network Structure of Goal Systems Predicts Human Performance

    Daniel Reichman, Falk Lieder, David D. Bourgin, Nimrod Talmon +1 more

    2023Cognitive Sciences2 citations

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49. An exploration of gradient-based features for buried threat detection using a handheld ground penetrating radar

    Evan Stump, Daniel Reichman, L. Collins, Jordan M. Malof

    2019Defense + Commercial Sensing2 citations

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50. How much shape information is enough, or too much? Designing imaging descriptors for threat detection in ground penetrating radar data

    Daniel Reichman, L. Collins, Jordan M. Malof

    2018Defense + Security2 citations

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