786 citations · 3k across the 61 of their papers we have counts for
5 papers · 1 filter
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems
Nimit S. Sohoni, Jared A. Dunnmon, Geoffrey Angus +2
In real-world classification tasks, each class often comprises multiple finer-grained "subclasses." As the subclass labels are frequently unavailable, models trained using only the…
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
Laurel Orr, Megan Leszczynski, Simran Arora +4
A challenge for named entity disambiguation (NED), the task of mapping textual mentions to entities in a knowledge base, is how to disambiguate entities that appear rarely in the t…
Leveraging Organizational Resources to Adapt Models to New Data Modalities
Sahaana Suri, Raghuveer Chanda, Neslihan Bulut +7
As applications in large organizations evolve, the machine learning (ML) models that power them must adapt the same predictive tasks to newly arising data modalities (e.g., a new v…
HiPPO: Recurrent Memory with Optimal Polynomial Projections
Albert Gu, Tri Dao, Stefano Ermon +2
A central problem in learning from sequential data is representing cumulative history in an incremental fashion as more data is processed. We introduce a general framework (HiPPO)…
GRIP: A Graph Neural Network Accelerator Architecture
Kevin Kiningham, Christopher Re, Philip Levis
We present GRIP, a graph neural network accelerator architecture designed for low-latency inference. AcceleratingGNNs is challenging because they combine two distinct types of comp…