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1The Next Generation of Machine Learning Tools | Roman Ring
Have you ever wondered how will the machine learning frameworks of the '20s look like? In this essay, I examine the directions AI research might take and the requirements they impose on the tools at our disposal, concluding with an overview of what I believe to be the two strong candidates: `JAX` and `S4TF`.
5 years ago by @analyst
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1What is Rust and why is it so popular? - Stack Overflow Blog
https://stackoverflow.blog/2020/01/20/what-is-rust-and-why-is-it-so-popular/
5 years ago by @analyst
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1Density-based Algorithms for Big Data Clustering Using MapReduce Framework
M. Khader, and G. Al-Naymat. ACM Computing Surveys, 53 (5): 1--38 (October 2020)
3 years ago by @analyst
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2020
clustering
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2020clusteringmap-reducerecommendationsoftware
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1Vehicle Trajectory Similarity
R. Sousa, A. Boukerche, and A. Loureiro. ACM Computing Surveys, 53 (5): 1--32 (October 2020)
3 years ago by @analyst
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geography
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2020geographygeometry
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1A Survey on Bayesian Deep Learning
H. Wang, and D. Yeung. ACM Computing Surveys, 53 (5): 1--37 (October 2020)
3 years ago by @analyst
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acm
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2020acmbayesiandeep-learningsurvey
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1Big Data Systems
A. Davoudian, and M. Liu. ACM Computing Surveys, 53 (5): 1--39 (October 2020)
3 years ago by @analyst
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acm
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software
2020acmmachine-learningsoftware
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1Parallel Genetic Algorithms
T. Harada, and E. Alba. ACM Computing Surveys, 53 (4): 1--39 (September 2020)
3 years ago by @analyst
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algorithm
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2020algorithmevolutionaryparallel
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1Understanding Optical Music Recognition
J. Calvo-Zaragoza, J. Jr., and A. Pacha. ACM Computing Surveys, 53 (4): 1--35 (September 2020)
3 years ago by @analyst
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machine-learning
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2020machine-learningmusic
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1A Survey of Learning Causality with Data
R. Guo, L. Cheng, J. Li, P. Hahn, and H. Liu. ACM Computing Surveys, 53 (4): 1--37 (September 2020)
3 years ago by @analyst
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1Causality-based Feature Selection
K. Yu, X. Guo, L. Liu, J. Li, H. Wang, Z. Ling, and X. Wu. ACM Computing Surveys, 53 (5): 1--36 (October 2020)
3 years ago by @analyst
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1Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
Y. Xie, J. Tian, and X. Zhu. IEEE Geoscience and Remote Sensing Magazine, 8 (4): 38-59 (December 2020)
4 years ago by @analyst
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3D
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2Contrastive Multi-View Representation Learning on Graphs
K. Hassani, and A. Khasahmadi. (2020)cite arxiv:2006.05582Comment: ICML 2020.
4 years ago by @analyst
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2Point2Mesh: A Self-Prior for Deformable Meshes
R. Hanocka, G. Metzer, R. Giryes, and D. Cohen-Or. (2020)cite arxiv:2005.11084Comment: SIGGRAPH 2020; Project page: https://ranahanocka.github.io/point2mesh/.
4 years ago by @analyst
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mesh
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2020meshpoint-cloudpytorchsiggraph
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1Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Reconstruction
K. Willis, Y. Pu, J. Luo, H. Chu, T. Du, J. Lambourne, A. Solar-Lezama, and W. Matusik. (2020)cite arxiv:2010.02392.
4 years ago by @analyst
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cad
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2020caddatasetreconstruction
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2Fast Construction of Discrete Geodesic Graphs
Y. Adikusuma, Z. Fang, and Y. He. ACM Transactions on Graphics, 39 (2): 1--14 (April 2020)
4 years ago by @analyst
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differential-geometry
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2020differential-geometrydiscretegraphsiggraph
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1Bijective projection in a shell
Z. Jiang, T. Schneider, D. Zorin, and D. Panozzo. ACM Transactions on Graphics, 39 (6): 1--18 (November 2020)
4 years ago by @analyst
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shell
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2A Laplacian for Nonmanifold Triangle Meshes
N. Sharp, and K. Crane. Comput. Graph. Forum, 39 (5): 69-80 (2020)
4 years ago by @analyst
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differential-geometry
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2020differential-geometrydiscretemanifoldsiggraph
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1Bézier guarding: Precise Higher-Order Meshing of Curved 2D Domains
M. Mandad, and M. Campen. ACM Transactions on Graphics, (July 2020)
4 years ago by @analyst
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bezier
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2020beziercurvegraphicssiggraph
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1Differentiable Rendering: A Survey
H. Kato, D. Beker, M. Morariu, T. Ando, T. Matsuoka, W. Kehl, and A. Gaidon. (2020)cite arxiv:2006.12057.
4 years ago by @analyst
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6NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
B. Mildenhall, P. Srinivasan, M. Tancik, J. Barron, R. Ramamoorthi, and R. Ng. (2020)cite arxiv:2003.08934Comment: ECCV 2020 (oral). Project page with videos and code: http://tancik.com/nerf.
4 years ago by @analyst
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NeRF
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1MINVO Basis: Finding Simplexes with Minimum Volume Enclosing Polynomial Curves
J. Tordesillas, and J. How. (2020)cite arxiv:2010.10726Comment: 17 pages, 16 figures.
4 years ago by @analyst
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geometry
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siggraph
2020geometrylinear-algebrasiggraph
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1Repulsive Curves
C. Yu, H. Schumacher, and K. Crane. (2020)cite arxiv:2006.07859Comment: 20 pages.
4 years ago by @analyst
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cmu
curve
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2020cmucurvegeometrygraphicssiggraph
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3TartanVO: A Generalizable Learning-based VO
W. Wang, Y. Hu, and S. Scherer. (2020)cite arxiv:2011.00359.
4 years ago by @analyst
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3D
multi-view
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3OccuSeg: Occupancy-aware 3D Instance Segmentation
L. Han, T. Zheng, L. Xu, and L. Fang. (2020)cite arxiv:2003.06537Comment: CVPR 2020, video this https URL https://youtu.be/co7y6LQ7Kqc.
4 years ago by @analyst
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1Updated science-wide author databases of standardized citation indicators
J. Ioannidis, K. Boyack, and J. Baas. PLOS Biology, 18 (10): 1-3 (October 2020)
4 years ago by @analyst
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2020comparisondatarankingscience
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1A New Geometric Subproblem to Extend Solvability of Inverse Kinematics Based on Screw Theory for 6R Robot Manipulators
J. Leoro, T. Hsiao, and C. Betancourt. International Journal of Control, Automation and Systems, (Sep 15, 2020)
4 years ago by @analyst
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geometry
kinematics
manipulator
physics
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2020geometrykinematicsmanipulatorphysicsroboticsspringer
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1Array programming with NumPy
C. Harris, K. Millman, S. van der Walt, R. Gommers, P. Virtanen, D. Cournapeau, E. Wieser, J. Taylor, S. Berg, N. Smith and 16 other author(s). Nature, 585 (7825): 357--362 (2020)
4 years ago by @analyst
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1Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications
N. Taleb. (2020)cite arxiv:2001.10488.
4 years ago by @analyst
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arxiv
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2020arxivbookstatistics
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1Essentials of Mathematical Methods: Foundations, Principles, and Algorithms
Y. Yang. (2020)
4 years ago by @analyst
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book
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pdf
2020bookdeep-learningmathematicspdf
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1Learning from Few Samples: A Survey
N. Bendre, H. Marín, and P. Najafirad. (2020)cite arxiv:2007.15484Comment: 17 pages, 10 figures.
4 years ago by @analyst
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deep-learning
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10Language Models are Few-Shot Learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell and 21 other author(s). (2020)cite arxiv:2005.14165Comment: 40+32 pages.
4 years ago by @analyst
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deep-learning
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2020deep-learningnlp
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2Crowdsourced 3D Mapping: A Combined Multi-View Geometry and Self-Supervised Learning Approach
H. Chawla, M. Jukola, T. Brouns, E. Arani, and B. Zonooz. (2020)cite arxiv:2007.12918Comment: Accepted at 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
4 years ago by @analyst
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2020deep-learningmulti-viewreconstructionself-supervised
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2Towards Learning Convolutions from Scratch
B. Neyshabur. (2020)cite arxiv:2007.13657Comment: 18 pages, 9 figures, 4 tables.
4 years ago by @analyst
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convolution
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2020convolutiondeep-learning
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2A Matrix Algebra Approach to Artificial Intelligence
X. Zhang. Springer Nature, (2020)
4 years ago by @analyst
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artificial-intelligence
linear-algebra
machine-learning
matrix
2020artificial-intelligencelinear-algebramachine-learningmatrix
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1Explaining Deep Neural Networks using Unsupervised Clustering
Y. Liu, and S. Arik. (2020)cite arxiv:2007.07477.
4 years ago by @analyst
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2020
clustering
deep-learning
2020clusteringdeep-learning
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3The Global Landscape of Neural Networks: An Overview
R. Sun, D. Li, S. Liang, T. Ding, and R. Srikant. (2020)cite arxiv:2007.01429Comment: 16 pages. 8 figures.
4 years ago by @analyst
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deep-learning
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2020deep-learningsurvey
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1Towards Robust Deep Learning with Ensemble Networks and Noisy Layers
Y. Liang, and R. Samavi. (2020)cite arxiv:2007.01507.
4 years ago by @analyst
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deep-learning
2020deep-learning
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1BOSH: Bayesian Optimization by Sampling Hierarchically
H. Moss, D. Leslie, and P. Rayson. (2020)cite arxiv:2007.00939.
4 years ago by @analyst
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bayesian
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sampling
2020bayesianoptimizationsampling
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1Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
K. Cao, Y. Chen, J. Lu, N. Arechiga, A. Gaidon, and T. Ma. (2020)cite arxiv:2006.15766.
4 years ago by @analyst
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dataset
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2Subspace approximation with outliers
A. Deshpande, and R. Pratap. (2020)cite arxiv:2006.16573.
4 years ago by @analyst
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approximation
linear-algebra
2020approximationlinear-algebra
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1Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights
S. Dave, R. Baghdadi, T. Nowatzki, S. Avancha, A. Shrivastava, and B. Li. (2020)cite arxiv:2007.00864.
4 years ago by @analyst
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2020
hardware
machine-learning
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tensor
2020hardwaremachine-learningsurveytensor
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2Sparse Gaussian Processes with Spherical Harmonic Features
V. Dutordoir, N. Durrande, and J. Hensman. (2020)cite arxiv:2006.16649Comment: International Conference on Machine, PMLR 119, 2020.
4 years ago by @analyst
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sphere
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1A Tutorial on VAEs: From Bayes' Rule to Lossless Compression
R. Yu. (2020)cite arxiv:2006.10273.
4 years ago by @analyst
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arxiv
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deep-learning
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2020arxivautoencoderdeep-learningtutorialvariational
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1Monte Carlo Geometry Processing: A Grid-Free Approach to PDE-Based Methods on Volumetric Domains
R. Sawhney, and K. Crane. ACM Trans. Graph., (2020)
4 years ago by @analyst
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geometry
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2The Unstoppable Rise of Computational Linguistics in Deep Learning
J. Henderson. (2020)cite arxiv:2005.06420Comment: 13 pages. Accepted for publication at ACL 2020, in the theme track.
4 years ago by @analyst
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deep-learning
linguistics
2020deep-learninglinguistics
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1Projectile Trajectory of Penguin's Faeces and Rectal Pressure Revisited
H. Tajima, and F. Fujisawa. (2020)cite arxiv:2007.00926Comment: 6 pages, 5 figures, accepted by Scientific and Educational Reports of the Faculty of Science and Technology, Kochi University.
4 years ago by @analyst
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arxiv
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2Unique Geometry and Texture from Corresponding Image Patches
D. Verbin, S. Gortler, and T. Zickler. (2020)cite arxiv:2003.08885.
4 years ago by @analyst
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geometry
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texture
2020geometryimage-processingtexture
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1Are there any 'object detectors' in the hidden layers of CNNs trained to identify objects or scenes?
E. Gale, N. Martin, R. Blything, A. Nguyen, and J. Bowers. (2020)cite arxiv:2007.01062Comment: Published in Vision Research 2020, 19 pages, 8 figures.
4 years ago by @analyst
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deep-learning
detection
2020deep-learningdetection
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2Isometric Autoencoders
M. Atzmon, A. Gropp, and Y. Lipman. (2020)cite arxiv:2006.09289.
4 years ago by @analyst
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2020
autoencoder
deep-learning
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2020autoencoderdeep-learninggeometry
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2Understanding Road Layout from Videos as a Whole
B. Liu, B. Zhuang, S. Schulter, P. Ji, and M. Chandraker. (2020)cite arxiv:2007.00822Comment: CVPR 2020.
4 years ago by @analyst
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deep-learning
video
2020deep-learningvideo
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1Consistent Structured Prediction with Max-Min Margin Markov Networks
A. Nowak-Vila, F. Bach, and A. Rudi. (2020)cite arxiv:2007.01012.
4 years ago by @analyst
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deep-learning
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2020deep-learningmarkovnetwork
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2Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning
Z. Ren, R. Yeh, and A. Schwing. (2020)cite arxiv:2007.01293.
4 years ago by @analyst
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2020datadatasetmachine-learningsemi-supervised
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