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Found 8 papers, 1 papers with code
Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity
With a simple argument, we obtain optimal or best-known complexity guarantees with cohypomonotonicity or weak MVI conditions for $\rho < \frac{1}{L}$.
NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and Bootstrapping
NeuJeans accelerates the performance of conv2d by up to 5. 68 times compared to state-of-the-art FHE-based PI work and performs the PI of a CNN at the scale of ImageNet (ResNet18) within a mere few seconds
Two-timescale Extragradient for Finding Local Minimax Points
Minimax problems are notoriously challenging to optimize.
HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Networks
Convolutional neural network (CNN) inference using fully homomorphic encryption (FHE) is a promising private inference (PI) solution due to the capability of FHE that enables offloading the whole computation process to the server while protecting the privacy of sensitive user data.
Hierarchical Text Classification As Sub-Hierarchy Sequence Generation
Consequently, these models are challenging to implement when the model parameters increase for a large-scale hierarchy because the model structure depends on the hierarchy size.
PAM:Point-wise Attention Module for 6D Object Pose Estimation
In GAP, it is designed to pay attention to important information in geometric information, and CAP is designed to pay attention to important information in Channel information.
Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs
We validate our Information Maximizing Hierarchical Conditional Variational AutoEncoder (Info-HCVAE) on several benchmark datasets by evaluating the performance of the QA model (BERT-base) using only the generated QA pairs (QA-based evaluation) or by using both the generated and human-labeled pairs (semi-supervised learning) for training, against state-of-the-art baseline models.
Ranked #1 on
Question Generation
on Natural Questions
Effective Crowdsourcing of Multiple Tasks for Comprehensive Knowledge Extraction
Information extraction from unstructured texts plays a vital role in the field of natural language processing.
