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Found 5 papers, 1 papers with code
Favour: FAst Variance Operator for Uncertainty Rating
Our contribution is a more principled variance propagation framework based on "spiked covariance matrices", which smoothly interpolates between quality and inference time.
Similarity Search with Tensor Core Units
Tensor Core Units (TCUs) are hardware accelerators developed for deep neural networks, which efficiently support the multiplication of two dense $\sqrt{m}\times \sqrt{m}$ matrices, where $m$ is a given hardware parameter.
Almost Optimal Tensor Sketch
With another construction we get $\lambda$ times more rows $m=\tilde O(c\,\lambda^2\,\varepsilon^{-2}(\log1/\delta)^3)$, but the matrix can be applied to any vector $x^{(1)}\otimes\dots\otimes x^{(c)}\in R^{d^c}$ in just $\tilde O(c\, (d+m))$ time.
Oblivious Sketching of High-Degree Polynomial Kernels
Oblivious sketching has emerged as a powerful approach to speeding up numerical linear algebra over the past decade, but our understanding of oblivious sketching solutions for kernel matrices has remained quite limited, suffering from the aforementioned exponential dependence on input parameters.
Data Structures and Algorithms
On the Complexity of Inner Product Similarity Join
* New upper and lower bounds for (A)LSH-based algorithms.
