{"list":"other","total":54,"rows":[{"id":"2002.05709","title":"A Simple Framework for Contrastive Learning of Visual Representations","created":"2020-02-13","cited_by_count":12049},{"id":"1503.02531","title":"Distilling the Knowledge in a Neural Network","created":"2015-03-09","cited_by_count":10324},{"id":"1703.03400","title":"Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks","created":"2017-03-09","cited_by_count":4897},{"id":"1503.03832","title":"FaceNet: A Unified Embedding for Face Recognition and Clustering","created":"2015-03-12","cited_by_count":2849},{"id":"1703.07737","title":"In Defense of the Triplet Loss for Person Re-Identification","created":"2017-03-22","cited_by_count":786},{"id":"2010.04592","title":"Contrastive Learning with Hard Negative Samples","created":"2020-10-09","cited_by_count":628},{"id":"1511.06452","title":"Deep Metric Learning via Lifted Structured Feature Embedding","created":"2015-11-19","cited_by_count":449},{"id":"1412.6622","title":"Deep metric learning using Triplet network","created":"2014-12-20","cited_by_count":422},{"id":"1903.03096","title":"Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples","created":"2019-03-07","cited_by_count":315},{"id":"1706.07567","title":"Sampling Matters in Deep Embedding Learning","created":"2017-06-23","cited_by_count":285},{"id":"1904.03436","title":"Unsupervised Embedding Learning via Invariant and Spreading Instance Feature","created":"2019-04-06","cited_by_count":232},{"id":"1703.07464","title":"No Fuss Distance Metric Learning using Proxies","created":"2017-03-21","cited_by_count":226},{"id":"1909.05235","title":"SoftTriple Loss: Deep Metric Learning Without Triplet Sampling","created":"2019-09-11","cited_by_count":163},{"id":"1608.04233","title":"A Riemannian Network for SPD Matrix Learning","created":"2016-08-15","cited_by_count":162},{"id":"1912.06798","title":"Cross-Batch Memory for Embedding Learning","created":"2019-12-14","cited_by_count":132},{"id":"1708.01682","title":"Deep Metric Learning with Angular Loss","created":"2017-08-04","cited_by_count":107},{"id":"2004.01113","title":"ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis","created":"2020-04-02","cited_by_count":107},{"id":"2003.08983","title":"A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses","created":"2020-03-19","cited_by_count":100},{"id":"1909.00900","title":"Metric Learning for Adversarial Robustness","created":"2019-09-03","cited_by_count":77},{"id":"1811.11819","title":"Unsupervised Meta-Learning For Few-Shot Image Classification","created":"2018-11-28","cited_by_count":75},{"id":"1904.04370","title":"Improved Embeddings with Easy Positive Triplet Mining","created":"2019-04-08","cited_by_count":67},{"id":"1306.6709","title":"A Survey on Metric Learning for Feature Vectors and Structured Data","created":"2013-06-28","cited_by_count":58},{"id":"2008.09164","title":"PyTorch Metric Learning","created":"2020-08-20","cited_by_count":57},{"id":"1903.11240","title":"Eigenvalue and Generalized Eigenvalue Problems: Tutorial","created":"2019-03-25","cited_by_count":46},{"id":"2106.08443","title":"Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nystr\\\"om Method, and Use of Kernels in Machine Learning: Tutorial and Survey","created":"2021-06-15","cited_by_count":37},{"id":"2004.12297","title":"Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document Matching","created":"2020-04-26","cited_by_count":35},{"id":"1512.09272","title":"Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions","created":"2015-12-31","cited_by_count":33},{"id":"2103.06638","title":"Generalized Contrastive Optimization of Siamese Networks for Place Recognition","created":"2021-03-11","cited_by_count":27},{"id":"1512.03622","title":"Deep Feature Learning with Relative Distance Comparison for Person Re-identification","created":"2015-12-11","cited_by_count":25},{"id":"1607.05002","title":"Geometric Mean Metric Learning","created":"2016-07-18","cited_by_count":22},{"id":"2101.00734","title":"Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey","created":"2021-01-04","cited_by_count":21},{"id":"2110.01858","title":"KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey","created":"2021-10-05","cited_by_count":16},{"id":"2004.04674","title":"Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks","created":"2020-04-05","cited_by_count":15},{"id":"2011.10925","title":"Locally Linear Embedding and its Variants: Tutorial and Survey","created":"2020-11-22","cited_by_count":15},{"id":"1907.03123","title":"Revisiting Metric Learning for Few-Shot Image Classification","created":"2019-07-06","cited_by_count":14},{"id":"2009.08136","title":"Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey","created":"2020-09-17","cited_by_count":13},{"id":"1906.03148","title":"Unsupervised and Supervised Principal Component Analysis: Tutorial","created":"2019-06-01","cited_by_count":12},{"id":"1906.09436","title":"Fisher and Kernel Fisher Discriminant Analysis: Tutorial","created":"2019-06-22","cited_by_count":12},{"id":"1908.04710","title":"metric-learn: Metric Learning Algorithms in Python","created":"2019-08-13","cited_by_count":11},{"id":"2011.00901","title":"Sampling Algorithms, from Survey Sampling to Monte Carlo Methods: Tutorial and Literature Review","created":"2020-11-02","cited_by_count":9},{"id":"1911.12425","title":"Learning with less data via Weakly Labeled Patch Classification in Digital Pathology","created":"2019-11-27","cited_by_count":8},{"id":"2106.02154","title":"Laplacian-Based Dimensionality Reduction Including Spectral Clustering, Laplacian Eigenmap, Locality Preserving Projection, Graph Embedding, and Diffusion Map: Tutorial and Survey","created":"2021-06-03","cited_by_count":8},{"id":"2005.08629","title":"Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study","created":"2020-05-10","cited_by_count":6},{"id":"2007.02200","title":"Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches","created":"2020-07-04","cited_by_count":6},{"id":"2107.12521","title":"Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey","created":"2021-07-26","cited_by_count":5},{"id":"2009.10301","title":"Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey","created":"2020-09-22","cited_by_count":4},{"id":"2111.13282","title":"Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey","created":"2021-11-26","cited_by_count":4},{"id":"1802.03170","title":"Adversarial Metric Learning","created":"2018-02-09","cited_by_count":3},{"id":"2009.14244","title":"Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling","created":"2020-09-29","cited_by_count":3},{"id":"1806.05454","title":"Low-rank geometric mean metric learning","created":"2018-06-14","cited_by_count":2},{"id":"1909.01651","title":"Metric Learning from Imbalanced Data","created":"2019-09-04","cited_by_count":2},{"id":"2007.05610","title":"Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem","created":"2020-07-10","cited_by_count":2},{"id":"1905.02102","title":"Improved Hard Example Mining by Discovering Attribute-based Hard Person Identity","created":"2019-05-06","cited_by_count":1},{"id":"2004.04573","title":"Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces","created":"2020-04-05","cited_by_count":1}],"next_cursor":null}