2 citations · 2 across the 4 of their papers we have counts for
4 papers
LampQ: Towards Accurate Layer-wise Mixed Precision Quantization for Vision Transformers
Minjun Kim, Jaeri Lee, Jongjin Kim +3
How can we accurately quantize a pre-trained Vision Transformer model? Quantization algorithms compress Vision Transformers (ViTs) into low-bit formats, reducing memory and computa…
Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating
Hyunsik Jeon, Jong-eun Lee, Jeongin Yun +1
How can we recommend cold-start bundles to users? The cold-start problem in bundle recommendation is crucial because new bundles are continuously created on the Web for various mar…
Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation
Jongjin Kim, Hyunsik Jeon, Jaeri Lee +1
When recommending personalized top- items to users, how can we recommend the items diversely to them while satisfying their needs? Aggregately diversified recommender systems ai…
Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledge
Hyunsik Jeon, Jongjin Kim, Hoyoung Yoon +2
How can we accurately recommend actions for users to control their devices at home? Action recommendation for smart home has attracted increasing attention due to its potential imp…