Search Results for author: Mohit Kumar

Found 15 papers, 2 papers with code

Membership-Mappings for Practical Secure Distributed Deep Learning

no code implementations12 Apr 2022 Mohit Kumar, Weiping Zhang, Lukas Fischer, Bernhard Freudenthaler

This study leverages the data representation capability of fuzzy based membership-mappings for practical secure distributed deep learning using fully homomorphic encryption.

Mental Stress Detection

Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation

no code implementations8 Feb 2022 Mohit Kumar, Samuel Kolb, Stefano Teso, Luc De Raedt

Combinatorial optimisation problems are ubiquitous in artificial intelligence.

Few-shot calibration of low-cost air pollution (PM2.5) sensors using meta-learning

1 code implementation2 Aug 2021 Kalpit Yadav, Vipul Arora, Sonu Kumar Jha, Mohit Kumar, Sachchida Nand Tripathi

Low-cost particulate matter sensors are transforming air quality monitoring because they have lower costs and greater mobility as compared to reference monitors.

Meta-Learning Transfer Learning

Learning Mixed-Integer Linear Programs from Contextual Examples

no code implementations15 Jul 2021 Mohit Kumar, Samuel Kolb, Luc De Raedt, Stefano Teso

In this paper, we study the problem of acquiring MILPs from contextual examples, a novel and realistic setting in which examples capture solutions and non-solutions within a specific context.

Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for Trustworthy AI

no code implementations6 Jun 2021 Mohit Kumar, Bernhard A. Moser, Lukas Fischer, Bernhard Freudenthaler

A variational membership-mapping Bayesian model is used for the analytical approximations of the defined information theoretic measures for privacy-leakage, interpretability, and transferability.

Heart Rate Variability Privacy Preserving

Differentially Private Transferrable Deep Learning with Membership-Mappings

no code implementations10 May 2021 Mohit Kumar

This paper considers the problem of differentially private semi-supervised transfer and multi-task learning.

Multi-Task Learning

Membership-Mappings for Data Representation Learning: Measure Theoretic Conceptualization

no code implementations14 Apr 2021 Mohit Kumar, Bernhard A. Moser, Lukas Fischer, Bernhard Freudenthaler

An analytical approach to the variational learning of a membership-mappings based data representation model is considered.

Representation Learning

Machine Guides, Human Supervises: Interactive Learning with Global Explanations

no code implementations21 Sep 2020 Teodora Popordanoska, Mohit Kumar, Stefano Teso

Compared to other explanatory interactive learning strategies, which are machine-initiated and rely on local explanations, XGL is designed to be robust against cases in which the explanations supplied by the machine oversell the classifier's quality.

Use of adaptive filtering techniques and deconvolution to obtain low range sidelobe samples

no code implementations10 Aug 2020 Mohit Kumar, V. Chandrasekar

In this paper the use of adaptive filtering techniques to obtain better peak sidelobe suppression and integrated sidelobe energy will be discussed with regard to weather radars and obtaining better sensitivity with this technique.

Toward Machine-Guided, Human-Initiated Explanatory Interactive Learning

no code implementations20 Jul 2020 Teodora Popordanoska, Mohit Kumar, Stefano Teso

This biases the "narrative" presented by the machine to the user. We address this narrative bias by introducing explanatory guided learning, a novel interactive learning strategy in which: i) the supervisor is in charge of choosing the query instances, while ii) the machine uses global explanations to illustrate its overall behavior and to guide the supervisor toward choosing challenging, informative instances.

Active Learning

Intermediate frequency Upgrade design features of NASA D3R Weather Radar System

no code implementations29 Feb 2020 Mohit Kumar, Shashank Joshil, Manuel Vega, Robert Beauchamp, V Chandrasekar

The NASA dual-frequency, dual-polarization, Doppler radar (D3R) is an important ground validation tool for the global precipitation measurement (GPM) mission dual-frequency precipitation radar (DPR).

Automating Personnel Rostering by Learning Constraints Using Tensors

no code implementations29 May 2018 Mohit Kumar, Stefano Teso, Luc De Raedt

Many problems in operations research require that constraints be specified in the model.

Decomposition Strategies for Constructive Preference Elicitation

1 code implementation22 Nov 2017 Paolo Dragone, Stefano Teso, Mohit Kumar, Andrea Passerini

We propose a decomposition technique for large preference-based decision problems relying exclusively on inference and feedback over partial configurations.

FairJudge: Trustworthy User Prediction in Rating Platforms

no code implementations30 Mar 2017 Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahamanian

We propose three metrics: (i) the fairness of a user that quantifies how trustworthy the user is in rating the products, (ii) the reliability of a rating that measures how reliable the rating is, and (iii) the goodness of a product that measures the quality of the product.

Fairness

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection

no code implementations19 Nov 2015 Bryan Hooi, Neil Shah, Alex Beutel, Stephan Gunnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos

To combine these 2 approaches, we formulate our Bayesian Inference for Rating Data (BIRD) model, a flexible Bayesian model of user rating behavior.

Bayesian Inference Fraud Detection

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