activity
20152022
most citedAn Adaptive Test of Independence with Analytic Kernel Embeddings

16 citations · 19 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20242 cited

Language Model Cascades: Token-level uncertainty and beyond

Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum +3

Recent advances in language models (LMs) have led to significant improvements in quality on complex NLP tasks, but at the expense of increased inference costs. Cascading offers a s…

cs.LG2023

It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models

Lin Chen, Michal Lukasik, Wittawat Jitkrittum +2

Classical wisdom in machine learning holds that the generalization error can be decomposed into bias and variance, and these two terms exhibit a \emph{trade-off}. However, in this…

cs.CV20223 cited

A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch

Patsorn Sangkloy, Wittawat Jitkrittum, Diyi Yang +1

We address the problem of retrieving images with both a sketch and a text query. We present TASK-former (Text And SKetch transformer), an end-to-end trainable model for image retri…

stat.ML201616 cited

An Adaptive Test of Independence with Analytic Kernel Embeddings

Wittawat Jitkrittum, Zoltan Szabo, Arthur Gretton

A new computationally efficient dependence measure, and an adaptive statistical test of independence, are proposed. The dependence measure is the difference between analytic embedd…

stat.ML2015

Passing Expectation Propagation Messages with Kernel Methods

Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess

We propose to learn a kernel-based message operator which takes as input all expectation propagation (EP) incoming messages to a factor node and produces an outgoing message. In or…