Neha Gupta | DeepAI

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∙ 07/06/2023

When Does Confidence-Based Cascade Deferral Suffice?

Cascades are a classical strategy to enable inference cost to vary adapt...

0 Wittawat Jitkrittum, et al. ∙

∙ 06/21/2022

Ensembling over Classifiers: a Bias-Variance Perspective

Ensembles are a straightforward, remarkably effective method for improvi...

0 Neha Gupta, et al. ∙

∙ 02/08/2022

Understanding the bias-variance tradeoff of Bregman divergences

This paper builds upon the work of Pfau (2013), which generalized the bi...

0 Ben Adlam, et al. ∙

∙ 11/03/2020

Estimating decision tree learnability with polylogarithmic sample complexity

We show that top-down decision tree learning heuristics are amenable to ...

0 Guy Blanc, et al. ∙

∙ 10/16/2020

Universal guarantees for decision tree induction via a higher-order splitting criterion

We propose a simple extension of top-down decision tree learning heurist...

0 Guy Blanc, et al. ∙

∙ 10/04/2020

Inapproximability for Local Correlation Clustering and Dissimilarity Hierarchical Clustering

We present hardness of approximation results for Correlation Clustering ...

0 Vaggos Chatziafratis, et al. ∙

∙ 09/23/2020

I-SiamIDS: an improved Siam-IDS for handling class imbalance in network-based intrusion detection systems

NIDSs identify malicious activities by analyzing network traffic. NIDSs ...

0 Punam Bedi, et al. ∙

∙ 09/07/2020

Projections for COVID-19 spread in India and its worst affected five states using the Modified SEIRD and LSTM models

The last leg of the year 2019 gave rise to a virus named COVID-19 (Coron...

0 Punam Bedi, et al. ∙

∙ 08/31/2020

Active Local Learning

In this work we consider active local learning: given a query point x, a...

9 Arturs Backurs, et al. ∙

∙ 08/13/2020

Fractional Poisson Processes of Order K

In this article, we introduce and study time- and space-fractional Poiss...

0 Neha Gupta, et al. ∙

∙ 04/19/2019

Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process

We consider deep networks, trained via stochastic gradient descent to mi...

0 Guy Blanc, et al. ∙

∙ 11/27/2018

Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression

In this paper, we obtain improved running times for regression and top e...

0 Neha Gupta, et al. ∙

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