Search Results for author:
Found 4 papers, 1 papers with code
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
This paper studies the curious phenomenon for machine learning models with Transformer architectures that their activation maps are sparse.
TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s
This paper presents a novel nearest neighbor search algorithm achieving TPU (Google Tensor Processing Unit) peak performance, outperforming state-of-the-art GPU algorithms with similar level of recall.
New Loss Functions for Fast Maximum Inner Product Search
In this work, we focus directly on minimizing error in inner product approximation and derive a new class of quantization loss functions.
Accelerating Large-Scale Inference with Anisotropic Vector Quantization
Based on the observation that for a given query, the database points that have the largest inner products are more relevant, we develop a family of anisotropic quantization loss functions.
