Summary of An Embedding Is Worth a Thousand Noisy Labels, by Francesco Di Salvo and Sebastian Doerrich and Ines Rieger and Christian Ledig
An Embedding is Worth a Thousand Noisy Labelsby Francesco Di Salvo, Sebastian Doerrich, Ines Rieger,…
An Embedding is Worth a Thousand Noisy Labelsby Francesco Di Salvo, Sebastian Doerrich, Ines Rieger,…
Contextual Bandits for Unbounded Context Distributionsby Puning Zhao, Jiafei Wu, Zhe Liu, Huiwen WuFirst submitted…
Image Clustering Algorithm Based on Self-Supervised Pretrained Models and Latent Feature Distribution Optimizationby Qiuyu Zhu,…
Data-Driven Machine Learning Approaches for Predicting In-Hospital Sepsis Mortalityby Arseniy Shumilov, Yueting Zhu, Negin Ashrafi,…
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Densityby Shuangqi Li, Chen…
On high-dimensional modifications of the nearest neighbor classifierby Annesha Ghosh, Deep Ghoshal, Bilol Banerjee, Anil…
Neurocache: Efficient Vector Retrieval for Long-range Language Modelingby Ali Safaya, Deniz YuretFirst submitted to arxiv…
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasksby Wataru Hashimoto, Hidetaka Kamigaito,…
ICM Ensemble with Novel Betting Functions for Concept Driftby Charalambos Eliades, Harris PapadopoulosFirst submitted to…
Separations in the Representational Capabilities of Transformers and Recurrent Architecturesby Satwik Bhattamishra, Michael Hahn, Phil…