Yueming Lyu

Orcid: 0000-0003-4028-5250

According to our database1, Yueming Lyu authored at least 29 papers between 2016 and 2024.

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Bibliography

2024
InfoStyler: Disentanglement Information Bottleneck for Artistic Style Transfer.
IEEE Trans. Circuits Syst. Video Technol., April, 2024

DRAN: Detailed Region-Adaptive Normalization for Conditional Image Synthesis.
IEEE Trans. Multim., 2024

Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation.
CoRR, 2024

Diversified Batch Selection for Training Acceleration.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Harmonizing Implicit Subpopulations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
3D-Aware Adversarial Makeup Generation for Facial Privacy Protection.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

Earning Extra Performance From Restrictive Feedbacks.
IEEE Trans. Pattern Anal. Mach. Intell., October, 2023

RS-Corrector: Correcting the Racial Stereotypes in Latent Diffusion Models.
CoRR, 2023

DeltaSpace: A Semantic-aligned Feature Space for Flexible Text-guided Image Editing.
CoRR, 2023

Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search.
CoRR, 2023

Adversary-Aware Partial label learning with Label distillation.
CoRR, 2023

DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation.
CoRR, 2023

Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Exploring Information Bottleneck for Weakly Supervised Semantic Segmentation.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2021
Efficient and Robust Black-box Integral-approximation and Optimization
PhD thesis, 2021

Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation.
Neural Comput., 2021

Detailed Region-Adaptive Normalization for Heavy Makeup Transfer.
CoRR, 2021

Neural Optimization Kernel: Towards Robust Deep Learning.
CoRR, 2021

Black-Box Optimizer with Stochastic Implicit Natural Gradient.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

SOGAN: 3D-Aware Shadow and Occlusion Robust GAN for Makeup Transfer.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Intrinsic Reward Driven Imitation Learning via Generative Model.
Proceedings of the 37th International Conference on Machine Learning, 2020

Curriculum Loss: Robust Learning and Generalization against Label Corruption.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Stochastic Implicit Natural Gradient for Black-box Optimization.
CoRR, 2019

Efficient Batch Black-box Optimization with Deterministic Regret Bounds.
CoRR, 2019

Marginalized Average Attentional Network for Weakly-Supervised Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2017
Spherical Structured Feature Maps for Kernel Approximation.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
A cone order sequence based multi-objective evolutionary algorithm.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016


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