> For the complete documentation index, see [llms.txt](https://gauravm.gitbook.io/about/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gauravm.gitbook.io/about/research/publications.md). # Publications FairGrad: Fairness Aware Gradient Descent.\ **Gaurav Maheshwari**, [Michaël Perrot](https://www.google.com/url?sa=t\&rct=j\&q=\&esrc=s\&source=web\&cd=\&cad=rja\&uact=8\&ved=2ahUKEwj67dOC_bv5AhWDxYUKHUdjCbQQFnoECA4QAQ\&url=https%3A%2F%2Fmperrot.github.io%2F\&usg=AOvVaw1Zvy-3SxwBL76z_vZZFMOw).\ TMLR, 2023\ [paper](https://arxiv.org/abs/2206.10923) */* [*github*](https://github.com/saist1993/fairgrad) */* [*docs*](https://fairgrad.readthedocs.io/en/latest/) */* [*pip*](https://pypi.org/project/fairgrad/) Fair Without Leveling Down: A New Intersectional Fairness Definition\ **Gaurav Maheshwari**, [Pascal Denis](http://researchers.lille.inria.fr/pdenis), [Mikaela Keller](https://www.cristal.univ-lille.fr/profil/kellerm), [Aurélien Bellet](http://researchers.lille.inria.fr/abellet)\ EMNLP, 2023 (Also presented at BIAS 2023 (ECML))\ [paper](https://hal.science/hal-04273353/document) Fair NLP Models with Differentially Private Text Encoders\ **Gaurav Maheshwari**, [Pascal Denis](http://researchers.lille.inria.fr/pdenis), [Mikaela Keller](https://www.cristal.univ-lille.fr/profil/kellerm), [Aurélien Bellet](http://researchers.lille.inria.fr/abellet)\ \&#xNAN;*EMNLP, 2022 (Findings)*\ [*paper*](https://arxiv.org/abs/2205.06135) */* [*github*](< https://github.com/saist1993/DPNLP>) Message Passing for Hyper-Relational Knowledge Graphs\ [Mikhail Galkin](https://migalkin.github.io/cv/), [Priyansh Trivedi](https://priyansh.page/), **Gaurav Maheshwari**, [Ricardo Usbeck](http://aksw.org/RicardoUsbeck.html), [Jens Lehmann](http://jens-lehmann.org/)\ \&#xNAN;*EMNLP, 2020*\ [*paper*](https://arxiv.org/abs/2009.10847) */* [*github*](https://github.com/migalkin/StarE) Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs\ [Nilesh Chakraborty](http://www.sda.cs.uni-bonn.de/people/nilesh-chakraborty/), [Denis Lukovnikov](http://sda.cs.uni-bonn.de/people/denis-lukovnikov/), **Gaurav Maheshwari,** [Priyansh Trivedi](https://priyansh.page/), [Jens Lehmann](http://jens-lehmann.org/), [Asja Fischer](https://www.ruhr-uni-bochum.de/ffm/Lehrstuehle/Machine_Learning/index.html.en)\ Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery\ [*paper*](http://jens-lehmann.org/files/2019/kbqa_nn_intro.pdf) Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs \ **Gaurav Maheshwari,** [Priyansh Trivedi](https://priyansh.page/)**,** [Denis Lukovnikov](http://sda.cs.uni-bonn.de/people/denis-lukovnikov/), [Nilesh Chakraborty](http://www.sda.cs.uni-bonn.de/people/nilesh-chakraborty/), [Asja Fischer](https://www.ruhr-uni-bochum.de/ffm/Lehrstuehle/Machine_Learning/index.html.en), [Jens Lehmann](http://jens-lehmann.org/)\ \&#xNAN;*ISWC, 2019*\ [*paper*](http://jens-lehmann.org/files/2019/iswc_complex_qa_ranking.pdf) */* [*github*](https://github.com/AskNowQA/KrantikariQA) A Question Answering System on Regulatory Documents\ [Diego Collarana](http://sda.cs.uni-bonn.de/people/diego-collarana/), Timm Heuss, [Jens Lehmann](http://jens-lehmann.org/), Ioanna Lytra, **Gaurav Maheshwari**, [Rostislav Nedelchev](http://www.sda.tech/Person/RostislavNedelchev/), Thorsten Schmidt, [Priyansh Trivedi](https://priyansh.page/)\ \&#xNAN;*JURIX, 2018*\ [*paper*](http://jens-lehmann.org/files/2018/jurix_qa.pdf) Formal Ontology Learning from English IS-A Sentences\ Sourish Dasgupta, Ankur Padia, **Gaurav Maheshwari**, [Priyansh Trivedi](https://priyansh.page/), [Jens Lehmann](http://jens-lehmann.org/)\ \&#xNAN;*arXiv Preprint*, 2018\ [*paper*](https://arxiv.org/pdf/1802.03701) LC-QuAD: A Corpus for Complex Question Answering over Knowledge Graphs\ [Priyansh Trivedi](https://priyansh.page/), **Gaurav Maheshwari**, [Mohnish Dubey](http://sda.cs.uni-bonn.de/people/mohnish-dubey/), [Jens Lehmann](http://sda.cs.uni-bonn.de/people/prof-dr-jens-lehmann/)\ \&#xNAN;*ISWC*, 2017 **(Spotlight)**\ [*paper*](http://lc-quad.sda.tech/static/ISWC2017_paper_152.pdf) */* [*code*](https://github.com/AskNowQA/LC-QuAD) */* [*webpage*](http://lc-quad.sda.tech/) */* [*slides*](https://docs.google.com/presentation/d/1pez_PK_NEDaZWf_N4gmqCkL_fT_JDibrAu4EBvdN_lU/edit?usp=sharing) SimDoc: Topic Sequence Alignment based Document Similarity Framework\ **Gaurav Maheshwari**, [Priyansh Trivedi](https://priyansh.page/), Harshita Sahijwani, Kunal Jha, [Sourish Dasgupta](https://www.linkedin.com/in/sourish-dasgupta-2432248/), [Jens Lehmann](http://sda.cs.uni-bonn.de/people/prof-dr-jens-lehmann/)\ \&#xNAN;*K-Cap*, 2017\ [*paper*](https://arxiv.org/pdf/1611.04822.pdf) / [code](https://github.com/saist1993/SimDoc) / [slides](https://docs.google.com/presentation/d/1RDonLji9iLjNy6DPXU0lp7jGtzWMdlxlqlTu2LDbKCk/edit?usp=sharing) Bidirectional LSTM with a Context Input Window for Named Entity Recognition in Tweets\ Rafael Peres, Diego Esteves, **Gaurav Maheshwari**\ \&#xNAN;*K-Cap*, 2017\ [*paper*](https://www.researchgate.net/profile/Diego_Esteves/publication/321897412_Bidirectional_LSTM_with_a_Context_Input_Window_for_Named_Entity_Recognition_in_Tweets/links/5a3a57020f7e9baa501aad79/Bidirectional-LSTM-with-a-Context-Input-Window-for-Named-Entity-Recognition-in-Tweets.pdf) BitSim: An Algebraic Similarity Measure for Description Logics Concepts\ Sourish Dasgupta, **Gaurav Maheshwari**, [Priyansh Trivedi](https://priyansh.page/)\ \&#xNAN;*arXiv Preprint*, 2015\ [*paper*](https://arxiv.org/pdf/1503.05667.pdf) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://gauravm.gitbook.io/about/research/publications.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. 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