Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Yoon, Minji"'
Autor:
Kumar, Rohan, Kim, Youngmin, Ravi, Sunitha, Sun, Haitian, Faloutsos, Christos, Salakhutdinov, Ruslan, Yoon, Minji
Pretrained Large Language Models (LLMs) have gained significant attention for addressing open-domain Question Answering (QA). While they exhibit high accuracy in answering questions related to common knowledge, LLMs encounter difficulties in learning
Externí odkaz:
http://arxiv.org/abs/2403.01382
Multimodal learning combines multiple data modalities, broadening the types and complexity of data our models can utilize: for example, from plain text to image-caption pairs. Most multimodal learning algorithms focus on modeling simple one-to-one pa
Externí odkaz:
http://arxiv.org/abs/2310.07478
As the field of Graph Neural Networks (GNN) continues to grow, it experiences a corresponding increase in the need for large, real-world datasets to train and test new GNN models on challenging, realistic problems. Unfortunately, such graph datasets
Externí odkaz:
http://arxiv.org/abs/2207.04396
In conference peer review, reviewers are often asked to provide "bids" on each submitted paper that express their interest in reviewing that paper. A paper assignment algorithm then uses these bids (along with other data) to compute a high-quality as
Externí odkaz:
http://arxiv.org/abs/2207.02303
Autor:
Yoon, Minji, Palowitch, John, Zelle, Dustin, Hu, Ziniu, Salakhutdinov, Ruslan, Perozzi, Bryan
Data continuously emitted from industrial ecosystems such as social or e-commerce platforms are commonly represented as heterogeneous graphs (HG) composed of multiple node/edge types. State-of-the-art graph learning methods for HGs known as heterogen
Externí odkaz:
http://arxiv.org/abs/2203.02018
Graph data is ubiquitous in academia and industry, from social networks to bioinformatics. The pervasiveness of graphs today has raised the demand for algorithms that can answer various questions: Which products would a user like to purchase given he
Externí odkaz:
http://arxiv.org/abs/2011.14925
Given a dynamic graph stream, how can we detect the sudden appearance of anomalous patterns, such as link spam, follower boosting, or denial of service attacks? Additionally, can we categorize the types of anomalies that occur in practice, and theore
Externí odkaz:
http://arxiv.org/abs/2011.13085
Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant time and memory? Existing approaches aim to detect individually surprisin
Externí odkaz:
http://arxiv.org/abs/2009.08452
Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant time and memory? Existing approaches aim to detect individually surprisin
Externí odkaz:
http://arxiv.org/abs/1911.04464
Autor:
Yoon, Minji, Park, Chanung
Publikováno v:
Journal of Asian Sociology, 2022 Mar 01. 51(1), 29-66.
Externí odkaz:
https://www.jstor.org/stable/27126206
