Search Results for author:
Found 8 papers, 3 papers with code
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning
In recent years, data selection has emerged as a core issue for large-scale visual-language model pretraining, especially on noisy web-curated datasets.
JoMA: Demystifying Multilayer Transformers via JOint Dynamics of MLP and Attention
We propose Joint MLP/Attention (JoMA) dynamics, a novel mathematical framework to understand the training procedure of multilayer Transformer architectures.
Improved Active Multi-Task Representation Learning via Lasso
In addition to our sample complexity results, we also characterize the potential of our $\nu^1$-based strategy in sample-cost-sensitive settings.
C-Mixup: Improving Generalization in Regression
In this paper, we propose a simple yet powerful algorithm, C-Mixup, to improve generalization on regression tasks.
CT-SGAN: Computed Tomography Synthesis GAN
Diversity in data is critical for the successful training of deep learning models.
MASAI: Multi-agent Summative Assessment Improvement for Unsupervised Environment Design
We qualitatively and quantitatively demonstrate that, in terms of multi-agent ($\geq$ 8 agents) navigation and steering, $\textit{Students}$ trained by our approach outperform agents using heuristic search, as well as agents trained by domain randomization.
Conditional Generation of Medical Images via Disentangled Adversarial Inference
Current practices in using cGANs for medical image generation, only use a single variable for image generation (i. e., content) and therefore, do not provide much flexibility nor control over the generated image.
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer Learning
The proposed algorithm achieved a mean accuracy of $87. 54\%$ and Cohen's kappa of $0. 8106$ in the slide-level classification of $305$ WSIs; performing better than a standard CNN and pathologists without gynecology-specific training.
