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Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation.

, , , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 1264-1274. PMLR, (2019)

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Learning Invariance with Compact Transforms., , , , and . ICLR (Workshop), OpenReview.net, (2018)Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees., , , , , , , and . NeurIPS, (2022)Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers., , , , , , and . NeurIPS, page 572-585. (2021)On the Downstream Performance of Compressed Word Embeddings., , , and . NeurIPS, page 11782-11793. (2019)Knowledge Distillation as Semiparametric Inference., , , and . ICLR, OpenReview.net, (2021)Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time., , , , , , , , , and 1 other author(s). ICML, volume 202 of Proceedings of Machine Learning Research, page 22137-22176. PMLR, (2023)Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps., , , , , , , and . CoRR, (2020)A Kernel Theory of Modern Data Augmentation., , , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 1528-1537. PMLR, (2019)Mamba: Linear-Time Sequence Modeling with Selective State Spaces, and . (2024)Hungry Hungry Hippos: Towards Language Modeling with State Space Models., , , , , and . ICLR, OpenReview.net, (2023)