Majid Hadian — accepted AI-conference papers

2026

TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate

Amir Zandieh, Majid Daliri, Majid Hadian, Vahab Mirrokni

ICLR 2026poster

Vector quantization, a problem rooted in Shannon's source coding theory, aims to quantize high-dimensional Euclidean vectors while minimizing distortion in their geometric structure. We propose TurboQuant to address both mean-squared error (MSE) and inner product distortion, overcoming limitations o…

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2024

MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding

Rajesh Jayaram, Laxman Dhulipala, Majid Hadian, Jason Lee, Vahab Mirrokni

NeurIPS 2024poster

Neural embedding models have become a fundamental component of modern information retrieval (IR) pipelines. These models produce a single embedding $x \in \mathbb{R}^d$ per data-point, allowing for fast retrieval via highly optimized maximum inner product search (MIPS) algorithms. Recently, beginnin…

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