113 citations · 397 across the 33 of their papers we have counts for
6 papers · 1 filter
Fine-Grained Object Detection over Scientific Document Images with Region Embeddings
Ankur Goswami, Joshua McGrath, Shanan Peters +1
We study the problem of object detection over scanned images of scientific documents. We consider images that contain objects of varying aspect ratios and sizes and range from coar…
Approximate Inference in Structured Instances with Noisy Categorical Observations
Alireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas
We study the problem of recovering the latent ground truth labeling of a structured instance with categorical random variables in the presence of noisy observations. We present a n…
Learning Functional Dependencies with Sparse Regression
Zhihan Guo, Theodoros Rekatsinas
We study the problem of discovering functional dependencies (FD) from a noisy dataset. We focus on FDs that correspond to statistical dependencies in a dataset and draw connections…
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models
Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha
Directed graphical models (DGMs) are a class of probabilistic models that are widely used for predictive analysis in sensitive domains, such as medical diagnostics. In this paper w…
HoloDetect: Few-Shot Learning for Error Detection
Alireza Heidari, Joshua McGrath, Ihab F. Ilyas +1
We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detectio…
MLSys: The New Frontier of Machine Learning Systems
Alexander Ratner, Dan Alistarh, Gustavo Alonso +66
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…