LiRank: Industrial Large Scale Ranking Models at LinkedIn

no code implementations • 10 Feb 2024 • Fedor Borisyuk, Mingzhou Zhou, Qingquan Song, Siyu Zhu, Birjodh Tiwana, Ganesh Parameswaran, Siddharth Dangi, Lars Hertel, Qiang Xiao, Xiaochen Hou, Yunbo Ouyang, Aman Gupta, Sheallika Singh, Dan Liu, Hailing Cheng, Lei Le, Jonathan Hung, Sathiya Keerthi, Ruoyan Wang, Fengyu Zhang, Mohit Kothari, Chen Zhu, Daqi Sun, Yun Dai, Xun Luan, Sirou Zhu, Zhiwei Wang, Neil Daftary, Qianqi Shen, Chengming Jiang, Haichao Wei, Maneesh Varshney, Amol Ghoting, Souvik Ghosh

We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods.

Click-Through Rate Prediction Quantization

Learning Macroscopic Brain Connectomes via Group-Sparse Factorization

1 code implementation • NeurIPS 2019 • Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar F. Caiafa, Russell Greiner, Martha White

We develop an efficient optimization strategy for this extremely high-dimensional sparse problem, by reducing the number of parameters using a greedy algorithm designed specifically for the problem.

Supervised autoencoders: Improving generalization performance with unsupervised regularizers

1 code implementation • NeurIPS 2018 • Lei Le, Andrew Patterson, Martha White

A common strategy to improve generalization has been through the use of regularizers, typically as a norm constraining the parameters.

The Utility of Sparse Representations for Control in Reinforcement Learning

no code implementations • 15 Nov 2018 • Vincent Liu, Raksha Kumaraswamy, Lei Le, Martha White

We investigate sparse representations for control in reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

Learning Sparse Representations in Reinforcement Learning with Sparse Coding

no code implementations • 26 Jul 2017 • Lei Le, Raksha Kumaraswamy, Martha White

Outside of reinforcement learning, sparse coding representations have been widely used, with non-convex objectives that result in discriminative representations.

reinforcement-learning Reinforcement Learning (RL) +1

Identifying global optimality for dictionary learning

no code implementations • 17 Apr 2016 • Lei Le, Martha White

We then provide an empirical investigation into practical optimization choices for using alternating minimization for induced DLMs, for both batch and stochastic gradient descent.

Dictionary Learning Matrix Completion

On predictability of rare events leveraging social media: a machine learning perspective

no code implementations • 20 Feb 2015 • Lei Le, Emilio Ferrara, Alessandro Flammini

However, extents and contexts in which such forecasting power can be effectively leveraged are still unverified at least in a systematic way.

BIG-bench Machine Learning Sentiment Analysis