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20202026
most citedOptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction

31 citations · 108 across the 34 of their papers we have counts for

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8 papers · 1 filter

cs.LG2026

The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project

Huamin Chen, Xunzhuo Liu, Bowei He +5

Over the past year, the vLLM Semantic Router project has released a series of work spanning: (1) core routing mechanisms -- signal-driven routing, context-length pool routing, rout…

cs.LG2025

Timing is Important: Risk-aware Fund Allocation based on Time-Series Forecasting

Fuyuan Lyu, Linfeng Du, Yunpeng Weng +6

Fund allocation has been an increasingly important problem in the financial domain. In reality, we aim to allocate the funds to buy certain assets within a certain future period. N…

cs.LG2024★ 12 cited

Toward a Better Understanding of Fourier Neural Operators from a Spectral Perspective

Shaoxiang Qin, Fuyuan Lyu, Wenhui Peng +7

In solving partial differential equations (PDEs), Fourier Neural Operators (FNOs) have exhibited notable effectiveness. However, FNO is observed to be ineffective with large Fourie…

cs.LG2024

ICE-SEARCH: A Language Model-Driven Feature Selection Approach

Tianze Yang, Tianyi Yang, Fuyuan Lyu +3

This study unveils the In-Context Evolutionary Search (ICE-SEARCH) method, which is among the first works that melds large language models (LLMs) with evolutionary algorithms for f…

cs.LG2023

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network

Fuyuan Lyu, Xing Tang, Dugang Liu +5

Deep sparse networks are widely investigated as a neural network architecture for prediction tasks with high-dimensional sparse features, with which feature interaction selection i…

cs.LG2023

Explicit Feature Interaction-aware Uplift Network for Online Marketing

Dugang Liu, Xing Tang, Han Gao +2

As a key component in online marketing, uplift modeling aims to accurately capture the degree to which different treatments motivate different users, such as coupons or discounts,…