1 code implementation • 3 Apr 2024 • Amirhossein Abaskohi, Amirhossein Dabiriaghdam, Lele Wang, Giuseppe Carenini
Memes, combining text and images, frequently use metaphors to convey persuasive messages, shaping public opinion.
no code implementations • 29 Mar 2024 • Wenliang Liu, Guanding Yu, Lele Wang, Renjie Liao
We study the Out-of-Distribution (OOD) generalization in machine learning and propose a general framework that provides information-theoretic generalization bounds.
no code implementations • 2 Jan 2024 • Bicheng Xu, Qi Yan, Renjie Liao, Lele Wang, Leonid Sigal
While previous works have explored image generation conditioned on scene graphs or layouts, our task is distinctive and important as it involves generating scene graphs themselves unconditionally from noise, enabling efficient and interpretable control for image generation.
no code implementations • 7 Sep 2023 • Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang
We consider the problem of computing a function of $n$ variables using noisy queries, where each query is incorrect with some fixed and known probability $p \in (0, 1/2)$.
1 code implementation • 4 Jul 2023 • Qi Yan, Zhengyang Liang, Yang song, Renjie Liao, Lele Wang
Diffusion models based on permutation-equivariant networks can learn permutation-invariant distributions for graph data.
no code implementations • 21 Jun 2023 • Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang
However, the upper and lower bounds do not match in terms of the dependence on $\delta$ and $p$.
1 code implementation • 2 Mar 2023 • Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao
To tackle these issues, we introduce Specformer, which effectively encodes the set of all eigenvalues and performs self-attention in the spectral domain, leading to a learnable set-to-set spectral filter.
no code implementations • 14 Feb 2023 • Jiaming Cheng, Duong Thuy Anh Nguyen, Lele Wang, Duong Tung Nguyen, Vijay K. Bhargava
Edge Computing (EC) offers a superior user experience by positioning cloud resources in close proximity to end users.
1 code implementation • 29 Jun 2022 • Lele Wang, Bin Liu
In this paper, we propose a novel adversarial en-semble training approach that jointly learns the label dependencies and member models.
no code implementations • 11 May 2021 • Animesh Sakorikar, Lele Wang
In this paper, we aim to overcome such limitations and construct gradient codes which exist for a wide range of system parameters while retaining the superior performance of BIBD gradient codes.