58 citations · 135 across the 31 of their papers we have counts for
35 papers
Random Fourier Features in Near-Linear Time
Sepideh Mahabadi, Sandeep Silwal, Tal Wagner
Random Fourier features approximate a shift-invariant kernel in , such as the Gaussian kernel , using independent samples from its spectra…
Locality Sensitive Hashing for p-Exponential Kernels with Applications to Density Estimation
Barak Gorodissky, Tal Wagner
A kernel is LSHable if there exists a locality sensitive hashing scheme such that for all . This notion plays a key role in effi…
Learning Query Encoders Can Be Hard Even When Vector Retrieval Is Geometrically Easy
Anders Wikum, Nina Mishra, Amin Saberi +1
Efficient vector retrieval requires both a corpus geometry that supports retrieving the right documents through vector similarity, and a query encoder that can embed queries near t…
QASP: Query-Adaptive Robust Vector Search Policy
Hakan Ferhatosmanoglu, Kushal Kumar, Tal Wagner +1
A fundamental challenge of vector search is achieving consistently high recall while minimizing computational costs. Fixed search parameters cause significant performance variance…
Frustratingly Simple Black-Box Adaptation of Language Models via Logit Bias
Ofek I. Cohen, Lior Shani, Aviv Rosenberg +3
Many organizations aim to adapt language models for internal use, both to improve performance on domain-specific tasks and to address privacy concerns around sensitive data. Howeve…
Positional LSH: Binary Block Matrix Approximation for Attention with Linear Biases
Daniel Wolfson, Tal Wagner
Positional encoding in transformers is commonly implemented through positional embeddings, attention masks, or bias terms, but formal connections between these mechanisms remain li…