Zohar Karnin | DeepAI

AI Chat

Featured Co-authors

Xin Huang
85 publications
Elad Hazan
65 publications
Vladimir Braverman
58 publications
Kevin Jamieson
50 publications
Rodolphe Jenatton
36 publications
Cedric Archambeau
35 publications
Graham Cormode
34 publications
Parminder Bhatia
33 publications
Krishnaram Kenthapadi
31 publications
Dotan Di Castro
23 publications
Shashank Singh
20 publications

∙ 09/07/2023

Uncovering Drift in Textual Data: An Unsupervised Method for Detecting and Mitigating Drift in Machine Learning Models

Drift in machine learning refers to the phenomenon where the statistical...

0 Saeed Khaki, et al. ∙

∙ 05/23/2022

Improving language models fine-tuning with representation consistency targets

Fine-tuning contextualized representations learned by pre-trained langua...

8 Anastasia Razdaibiedina, et al. ∙

∙ 03/27/2022

Pyramid-BERT: Reducing Complexity via Successive Core-set based Token Selection

Transformer-based language models such as BERT have achieved the state-o...

3 Xin Huang, et al. ∙

∙ 11/26/2021

Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models

With the increasing adoption of machine learning (ML) models and systems...

0 David Nigenda, et al. ∙

∙ 07/23/2021

Improving Early Sepsis Prediction with Multi Modal Learning

Sepsis is a life-threatening disease with high morbidity, mortality and ...

25 Fred Qin, et al. ∙

∙ 12/15/2020

Amazon SageMaker Autopilot: a white box AutoML solution at scale

AutoML systems provide a black-box solution to machine learning problems...

0 Piali Das, et al. ∙

∙ 12/11/2020

TabTransformer: Tabular Data Modeling Using Contextual Embeddings

We propose TabTransformer, a novel deep tabular data modeling architectu...

8 Xin Huang, et al. ∙

∙ 11/11/2020

GANMEX: One-vs-One Attributions using GAN-based Model Explainability

Attribution methods have been shown as promising approaches for identify...

8 Sheng-Min Shih, et al. ∙

∙ 07/27/2020

Practical and sample efficient zero-shot HPO

Zero-shot hyperparameter optimization (HPO) is a simple yet effective us...

9 Fela Winkelmolen, et al. ∙

∙ 06/21/2020

An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits

This paper proposes near-optimal algorithms for the pure-exploration lin...

0 Julian Katz-Samuels, et al. ∙

∙ 05/22/2020

PruneNet: Channel Pruning via Global Importance

Channel pruning is one of the predominant approaches for accelerating de...

0 Ashish Khetan, et al. ∙

∙ 05/09/2020

schuBERT: Optimizing Elements of BERT

Transformers <cit.> have gradually become a key component for many state...

0 Ashish Khetan, et al. ∙

∙ 04/03/2020

Relative Error Streaming Quantiles

Approximating ranks, quantiles, and distributions over streaming data is...

0 Graham Cormode, et al. ∙

∙ 06/29/2019

Streaming Quantiles Algorithms with Small Space and Update Time

Approximating quantiles and distributions over streaming data has been s...

0 Nikita Ivkin, et al. ∙

∙ 06/22/2019

Asymmetric Random Projections

Random projections (RP) are a popular tool for reducing dimensionality w...

0 Nick Ryder, et al. ∙

∙ 06/11/2019

Discrepancy, Coresets, and Sketches in Machine Learning

This paper defines the notion of class discrepancy for families of funct...

0 Zohar Karnin, et al. ∙

∙ 05/20/2019

DARC: Differentiable ARchitecture Compression

In many learning situations, resources at inference time are significant...

0 Shashank Singh, et al. ∙

∙ 07/05/2016

One-Shot Session Recommendation Systems with Combinatorial Items

In recent years, content recommendation systems in large websites (or co...

0 Yahel David, et al. ∙

∙ 06/29/2016

How Many Folders Do You Really Need?

Email classification is still a mostly manual task. Consequently, most W...

0 Mihajlo Grbovic, et al. ∙

∙ 12/21/2013

Volumetric Spanners: an Efficient Exploration Basis for Learning

Numerous machine learning problems require an exploration basis - a mech...

0 Elad Hazan, et al. ∙

∙ 11/19/2013

Near-Optimal Entrywise Sampling for Data Matrices

We consider the problem of selecting non-zero entries of a matrix A in o...

0 Dimitris Achlioptas, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world