Search Results for author:
Found 14 papers, 1 papers with code
SAM2-ELNet: Label Enhancement and Automatic Annotation for Remote Sensing Segmentation
The performance of existing supervised models in remote sensing image segmentation tasks highly depends on the quality of label data.
Differentially Private Equilibrium Finding in Polymatrix Games
We study equilibrium finding in polymatrix games under differential privacy constraints.
DiffETM: Diffusion Process Enhanced Embedded Topic Model
The embedded topic model (ETM) is a widely used approach that assumes the sampled document-topic distribution conforms to the logistic normal distribution for easier optimization.
UniRiT: Towards Few-Shot Non-Rigid Point Cloud Registration
In this work, we aim to deal with this challenging few-shot non-rigid point cloud registration problem.
Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling
Large language models (LLMs) exhibit varying strengths and weaknesses across different tasks, prompting recent studies to explore the benefits of ensembling models to leverage their complementary advantages.
GERA: Geometric Embedding for Efficient Point Registration Analysis
Point cloud registration aims to provide estimated transformations to align point clouds, which plays a crucial role in pose estimation of various navigation systems, such as surgical guidance systems and autonomous vehicles.
LiteEFG: An Efficient Python Library for Solving Extensive-form Games
LiteEFG is an efficient library with easy-to-use Python bindings, which can solve multiplayer extensive-form games (EFGs).
Transformer-based Single-Cell Language Model: A Survey
In this review, we attempt to systematically summarize the single-cell language models and applications based on transformers.
Privacy in LLM-based Recommendation: Recent Advances and Future Directions
Nowadays, large language models (LLMs) have been integrated with conventional recommendation models to improve recommendation performance.
RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation
We propose two approaches based on reward and preference aggregation, respectively: the former utilizes both utilitarianism and Leximin approaches to aggregate individual reward models, with sample complexity guarantees; the latter directly aggregates the human feedback in the form of probabilistic opinions.
Human Emotion Recognition Based On Galvanic Skin Response signal Feature Selection and SVM
A novel human emotion recognition method based on automatically selected Galvanic Skin Response (GSR) signal features and SVM is proposed in this paper.
The Power of Regularization in Solving Extensive-Form Games
Second, we show that regularized counterfactual regret minimization (\texttt{Reg-CFR}), with a variant of optimistic mirror descent algorithm as regret-minimizer, can achieve $O(1/T^{1/4})$ best-iterate, and $O(1/T^{3/4})$ average-iterate convergence rate for finding NE in EFGs.
CCAT-NET: A Novel Transformer Based Semi-supervised Framework for Covid-19 Lung Lesion Segmentation
In this work, we propose a novel network structure that combines CNN and Transformer for the segmentation of COVID-19 lesions.
Safe Opponent-Exploitation Subgame Refinement
Search algorithms have been playing a vital role in the success of superhuman AI in both perfect information and imperfect information games.
