15 citations · 51 across the 40 of their papers we have counts for
8 papers · 1 filter
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…
Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning
Fangzhou Wu, Haike Xu, Sandeep Silwal
Graph-based approximate nearest neighbor search (ANNS) is widely used for large-scale semantic search. Its indices are constructed primarily based on geometric relationships among…
Dynamic estimation of slowly varying sequences
Prashant Gokhale, Mikhail Khodak, Sandeep Silwal
We consider the problem of sequentially approximating functions of each element in a slowly-varying sequence, i.e. one where the magnitude of the difference between the eleme…
Compact Geometric Representations of Hierarchies
Prashant Gokhale, Piotr Indyk, Yuhao Liu +3
Computing geometric representations of data is a cornerstone of modern machine learning, typically achieved by training dual encoders which map queries and documents into a shared…
Capturing LLM Capabilities via Evidence-Calibrated Query Clustering
Fangzhou Wu, Sandeep Silwal, Qiuyi Zhang
Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing clustering methods, which primarily…
DynMuon: A Dynamic Spectral Shaping View of Muon
Fangzhou Wu, Rikhav Shah, Sandeep Silwal +1
In recent years, Muon has emerged as the dominant method for training large language models, and transformers more broadly. The essential difference, when compared to standard grad…