Search Results for author: Erik Lindgren

Found 4 papers, 2 papers with code

Efficient Training of Retrieval Models using Negative Cache

2 code implementations NeurIPS 2021 Erik Lindgren, Sashank Reddi, Ruiqi Guo, Sanjiv Kumar

These models are typically trained by optimizing the model parameters to score relevant positive" pairs higher than the irrelevantnegative" ones.

Information Retrieval Retrieval

On $\infty$-Ground States in the Plane

no code implementations17 Feb 2021 Erik Lindgren, Peter Lindqvist

We study $\infty$-Ground states in convex domains in the plane.

Analysis of PDEs 35K65, 35P30, 35J70

Approximate Probabilistic Inference with Composed Flows

no code implementations28 Sep 2020 Jay Whang, Erik Lindgren, Alex Dimakis

We study the problem of probabilistic inference on the joint distribution defined by a normalizing flow model.

Variational Inference

Accelerating Large-Scale Inference with Anisotropic Vector Quantization

3 code implementations ICML 2020 Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar

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.

Benchmarking Quantization

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