Chun-Nam Yu

22 papers A* 3A 2B 1Journal 11Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Monkey Jump : MoE-Style PEFT for Efficient Multi-Task Learning.
CoRR
Nusrat Jahan Prottasha, Md Kowsher, Chun-Nam Yu, Chen Chen, Ozlem O. Garibay
2025 — conf
Does Self-Attention Need Separate Weights in Transformers?
NAACL (Industry Track)
Md. Kowsher, Nusrat Jahan Prottasha, Chun-Nam Yu, Ozlem O. Garibay, Niloofar Yousefi
2025 — conf
Predicting Through Generation: Why Generation Is Better for Prediction.
ACL (1)
Md. Kowsher, Nusrat Jahan Prottasha, Prakash Bhat, Chun-Nam Yu, Mojtaba Soltanalian, Ivan Garibay, Ozlem O. Garibay, Chen Chen, Niloofar Yousefi
2025 J jnl
Predicting Through Generation: Why Generation Is Better for Prediction.
CoRR
Md. Kowsher, Nusrat Jahan Prottasha, Prakash Bhat, Chun-Nam Yu, Mojtaba Soltanalian, Ivan Garibay, Ozlem O. Garibay, Chen Chen, Niloofar Yousefi
2025 — conf
RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates.
ACL (1)
Md. Kowsher, Tara Esmaeilbeig, Chun-Nam Yu, Chen Chen, Mojtaba Soltanalian, Niloofar Yousefi
2024 J jnl
Does Self-Attention Need Separate Weights in Transformers?
CoRR
Md. Kowsher, Nusrat Jahan Prottasha, Chun-Nam Yu, Ozlem O. Garibay, Niloofar Yousefi
2024 J jnl
RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates.
CoRR
Md. Kowsher, Tara Esmaeilbeig, Chun-Nam Yu, Mojtaba Soltanalian, Niloofar Yousefi
2022 J jnl
A Study on Representation Transfer for Few-Shot Learning.
CoRR
Chun-Nam Yu, Yi Xie
2019 — conf
A Direct Approach to Robust Deep Learning Using Adversarial Networks.
ICLR (Poster)
Huaxia Wang, Chun-Nam Yu
2019 J jnl
A Direct Approach to Robust Deep Learning Using Adversarial Networks.
CoRR
Huaxia Wang, Chun-Nam Yu
2019 J jnl
DyMo: Dynamic Monitoring of Large-Scale LTE-Multicast Systems.
IEEE/ACM Trans. Netw.
Yigal Bejerano, Chandrashekhar Raman, Chun-Nam Yu, Varun Gupta, Craig Gutterman, Tomas Young, Hugo Infante, Yousef Abdelmalek, Gil Zussman
2017 J jnl
A Sparse Coding Approach to Household Electricity Demand Forecasting in Smart Grids.
IEEE Trans. Smart Grid
Chun-Nam Yu, Piotr Mirowski, Tin Kam Ho
2017 A conf
Convolutional Neural Networks for Figure Extraction in Historical Technical Documents.
ICDAR
Chun-Nam Yu, Caleb Carson Levy, Iraj Saniee
2017 J jnl
DyMo: Dynamic Monitoring of Large Scale LTE-Multicast Systems.
CoRR
Yigal Bejerano, Chandru Raman, Chun-Nam Yu, Varun Gupta, Craig Gutterman, Tomas Young, Hugo Infante, Yousef Abdelmalek, Gil Zussman
2017 A* conf
DyMo: Dynamic monitoring of large scale LTE-Multicast systems.
INFOCOM
Yigal Bejerano, Chandru Raman, Chun-Nam Yu, Varun Gupta, Craig Gutterman, Tomas Young, Hugo Infante, Yousef Abdelmalek, Gil Zussman
2016 B conf
Online Algorithm for Approximate Quantile Queries on Sliding Windows.
SEA
Chun-Nam Yu, Michael S. Crouch, Ruichuan Chen, Alessandra Sala
2014 J jnl
Demand Forecasting in Smart Grids.
Bell Labs Tech. J.
Piotr Mirowski, Sining Chen, Tin Kam Ho, Chun-Nam Yu
2014 A* conf
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification.
ICML
Junfeng Wen, Chun-Nam Yu, Russell Greiner
2012 J jnl
A Generalized Loop Correction Method for Approximate Inference in Graphical Models
CoRR
Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner
2012 A* conf
A Generalized Loop Correction Method for Approximate Inference in Graphical Models.
ICML
Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner
2012 A conf
Transductive Learning of Structural SVMs via Prior Knowledge Constraints.
AISTATS
Chun-Nam Yu
2011 — conf
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors.
NIPS
Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin, Vickie Baracos