21 citations · 43 across the 30 of their papers we have counts for
10 papers · 1 filter
Query-efficient model evaluation using cached responses
Hayden Helm, Ben Johnson, Carey Priebe
Evaluating a new model on an existing benchmark is often necessary to understand its behavior before deployment. For modern evaluation frameworks, generating and evaluating a respo…
Black-box model classification under the discriminative factorization
Hayden Helm, Merrick Ohata, Carey Priebe
Access to modern generative systems is often restricted to querying an API (the ``black-box" setting) and many properties of the system are unknown to the user at inference time. W…
Statistical inference on black-box generative models in the data kernel perspective space
Hayden Helm, Aranyak Acharyya, Brandon Duderstadt +2
Generative models are capable of producing human-expert level content across a variety of topics and domains. As the impact of generative models grows, it is necessary to develop s…
Consistent estimation of generative model representations in the data kernel perspective space
Aranyak Acharyya, Michael W. Trosset, Carey E. Priebe +1
Generative models, such as large language models and text-to-image diffusion models, produce relevant information when presented a query. Different models may produce different inf…
Comparing Foundation Models using Data Kernels
Brandon Duderstadt, Hayden S. Helm, Carey E. Priebe
Recent advances in self-supervised learning and neural network scaling have enabled the creation of large models, known as foundation models, which can be easily adapted to a wide…
Deep Learning with Label Noise: A Hierarchical Approach
Li Chen, Ningyuan Huang, Cong Mu +4
Deep neural networks are susceptible to label noise. Existing methods to improve robustness, such as meta-learning and regularization, usually require significant change to the net…
Leveraging semantically similar queries for ranking via combining representations
Hayden S. Helm, Marah Abdin, Benjamin D. Pedigo +8
In modern ranking problems, different and disparate representations of the items to be ranked are often available. It is sensible, then, to try to combine these representations to…
Subgraph nomination: Query by Example Subgraph Retrieval in Networks
Al-Fahad M. Al-Qadhi, Carey E. Priebe, Hayden S. Helm +1
This paper introduces the subgraph nomination inference task, in which example subgraphs of interest are used to query a network for similarly interesting subgraphs. This type of p…
Distance-based Positive and Unlabeled Learning for Ranking
Hayden S. Helm, Amitabh Basu, Avanti Athreya +12
Learning to rank -- producing a ranked list of items specific to a query and with respect to a set of supervisory items -- is a problem of general interest. The setting we consider…
Random Forests for Adaptive Nearest Neighbor Estimation of Information-Theoretic Quantities
Ronan Perry, Ronak Mehta, Richard Guo +6
Information-theoretic quantities, such as conditional entropy and mutual information, are critical data summaries for quantifying uncertainty. Current widely used approaches for co…