19 citations · 40 across the 13 of their papers we have counts for
16 papers
Best-of-Better-: Generating Pre-Aligned Responses with In-Context Learning
Eric Lei, Hsiang Hsu, Chun-Fu Chen
Inference-time alignment methods, such as Best-of-, offer a flexible alternative to training-based alignment by using reward models to select high-quality responses generated by…
Best-of-Tails: Bridging Optimism and Pessimism in Inference-Time Alignment
Hsiang Hsu, Eric Lei, Chun-Fu Chen
Inference-time alignment effectively steers large language models (LLMs) by generating multiple candidates from a reference model and selecting among them with an imperfect reward…
Optimal Neural Compressors for the Rate-Distortion-Perception Tradeoff
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
Recent efforts in neural compression have focused on the rate-distortion-perception (RDP) tradeoff, where the perception constraint ensures the source and reconstruction distributi…
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
Neural compression has brought tremendous progress in designing lossy compressors with good rate-distortion (RD) performance at low complexity. Thus far, neural compression design…
Score-Based Methods for Discrete Optimization in Deep Learning
Eric Lei, Arman Adibi, Hamed Hassani
Discrete optimization problems often arise in deep learning tasks, despite the fact that neural networks typically operate on continuous data. One class of these problems involve o…
WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
Eric Lei, Muhammad Asad Lodhi, Jiahao Pang +2
There have been recent efforts to learn more meaningful representations via fixed length codewords from mesh data, since a mesh serves as a complete model of underlying 3D shape co…
Text + Sketch: Image Compression at Ultra Low Rates
Eric Lei, Yiğit Berkay Uslu, Hamed Hassani +1
Recent advances in text-to-image generative models provide the ability to generate high-quality images from short text descriptions. These foundation models, when pre-trained on bi…
On a Relation Between the Rate-Distortion Function and Optimal Transport
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
We discuss a relationship between rate-distortion and optimal transport (OT) theory, even though they seem to be unrelated at first glance. In particular, we show that a function d…
Federated Neural Compression Under Heterogeneous Data
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
We discuss a federated learned compression problem, where the goal is to learn a compressor from real-world data which is scattered across clients and may be statistically heteroge…
Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
A fundamental question in designing lossy data compression schemes is how well one can do in comparison with the rate-distortion function, which describes the known theoretical lim…
Robust Graph Neural Networks via Probabilistic Lipschitz Constraints
Raghu Arghal, Eric Lei, Shirin Saeedi Bidokhti
Graph neural networks (GNNs) have recently been demonstrated to perform well on a variety of network-based tasks such as decentralized control and resource allocation, and provide…
Out-of-Distribution Robustness in Deep Learning Compression
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
In recent years, deep neural network (DNN) compression systems have proved to be highly effective for designing source codes for many natural sources. However, like many other mach…
CSI-Based Multi-Antenna and Multi-Point Indoor Positioning Using Probability Fusion
Emre Gönültaş, Eric Lei, Jack Langerman +2
Channel state information (CSI)-based fingerprinting via neural networks (NNs) is a promising approach to enable accurate indoor and outdoor positioning of user equipments (UEs), e…
Siamese Neural Networks for Wireless Positioning and Channel Charting
Eric Lei, Oscar Castañeda, Olav Tirkkonen +2
Neural networks have been proposed recently for positioning and channel charting of user equipments (UEs) in wireless systems. Both of these approaches process channel state inform…
Novel Prediction Techniques Based on Clusterwise Linear Regression
Igor Gitman, Jieshi Chen, Eric Lei +1
In this paper we explore different regression models based on Clusterwise Linear Regression (CLR). CLR aims to find the partition of the data into clusters, such that linear re…
Characterization of Hemodynamic Signal by Learning Multi-View Relationships
Eric Lei, Kyle Miller, Michael R. Pinsky +1
Multi-view data are increasingly prevalent in practice. It is often relevant to analyze the relationships between pairs of views by multi-view component analysis techniques such as…