Search Results for author:
Found 14 papers, 5 papers with code
Learning the irreversible progression trajectory of Alzheimer's disease
Specifically, we introduce a monotonicity constraint that encourages the model to predict disease risk in a consistent and ordered manner across follow-up visits.
Hierarchical Query Classification in E-commerce Search
E-commerce platforms typically store and structure product information and search data in a hierarchy.
Implicit-explicit Integrated Representations for Multi-view Video Compression
To further enhance the reconstruction quality from the INR codec, we leverage the high-quality reconstructed frames from the explicit codec to achieve inter-view compensation.
A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification
Immune repertoire classification, a typical multiple instance learning (MIL) problem, is a frontier research topic in computational biology that makes transformative contributions to new vaccines and immune therapies.
DNAGPT: A Generalized Pre-trained Tool for Versatile DNA Sequence Analysis Tasks
Pre-trained large language models demonstrate potential in extracting information from DNA sequences, yet adapting to a variety of tasks and data modalities remains a challenge.
Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation
In this work, we create two novel datasets of misinformation and counter-misinformation response pairs from in-the-wild social media and crowdsourcing from college-educated students.
Learning with Noisy Labels over Imbalanced Subpopulations
Then, we refurbish the noisy labels using the estimated clean probabilities and the pseudo-labels from the model's predictions.
Blood-derived lncRNAs as potential biomarkers for early cancer diagnosis: The Good, the Bad and the Beauty
Cancer ranks as one of the deadliest diseases worldwide.
ASGARD: A Single-cell Guided pipeline to Aid Repurposing of Drugs
Intercellular heterogeneity is a major obstacle to successful precision medicine.
PETGEN: Personalized Text Generation Attack on Deep Sequence Embedding-based Classification Models
Here we create a novel adversarial attack model against deep user sequence embedding based classification models, which use the sequence of user posts to generate user embeddings and detect malicious users.
The Role of the Crowd in Countering Misinformation: A Case Study of the COVID-19 Infodemic
Concerned citizens (i. e., the crowd), who are users of the platforms where misinformation appears, can play a crucial role in disseminating fact-checking information and in countering the spread of misinformation.
Racism is a Virus: Anti-Asian Hate and Counterspeech in Social Media during the COVID-19 Crisis
The spread of COVID-19 has sparked racism and hate on social media targeted towards Asian communities.
Prediction of repurposed drugs for treating lung injury in COVID-19
Further bioinformatics analysis shows that twelve significantly enriched pathways (P-value <0. 05) overlap between HCC515 cells treated with ACE2 inhibitor and human COVID-19 patient lung tissues, including signaling pathways known to be associated with lung injury such as TNF signaling, MAPK signaling and Chemokine signaling pathways.
Part-Regularized Near-Duplicate Vehicle Re-Identification
Our framework is trained end-to-end with combined local and global constrains.
