Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Adrian Weller

University of Cambridge, The Alan Turing Institute

On the Fairness of Causal Algorithmic Recourse

Oct 14, 2020
Julius von K√ľgelgen, Umang Bhatt, Amir-Hossein Karimi, Isabel Valera, Adrian Weller, Bernhard Sch√∂lkopf


  Access Paper or Ask Questions

Rethinking Attention with Performers

Sep 30, 2020
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy Colwell, Adrian Weller

* 36 pages. This is an updated version of a previous submission which can be found at arXiv:2006.03555. See https://github.com/google-research/google-research/tree/master/protein_lm for protein language model code, and https://github.com/google-research/google-research/tree/master/performer for Performer code 

  Access Paper or Ask Questions

Machine Learning Explainability for External Stakeholders

Jul 10, 2020
Umang Bhatt, McKane Andrus, Adrian Weller, Alice Xiang


  Access Paper or Ask Questions

An Ode to an ODE

Jun 23, 2020
Krzysztof Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani

* 20 pages, 9 figures 

  Access Paper or Ask Questions

Getting a CLUE: A Method for Explaining Uncertainty Estimates

Jun 11, 2020
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato

* 33 pages, 31 figures 

  Access Paper or Ask Questions

UFO-BLO: Unbiased First-Order Bilevel Optimization

Jun 05, 2020
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Davis, Adrian Weller


  Access Paper or Ask Questions

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers

Jun 05, 2020
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamas Sarlos, David Belanger, Lucy Colwell, Adrian Weller

* 14 pages, 11 figures 

  Access Paper or Ask Questions

Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks

May 11, 2020
Moein Khajehnejad, Ahmad Asgharian Rezaei, Mahmoudreza Babaei, Jessica Hoffmann, Mahdi Jalili, Adrian Weller

* In Proc. of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), 2020 

  Access Paper or Ask Questions

Time Dependence in Non-Autonomous Neural ODEs

May 06, 2020
Jared Quincy Davis, Krzysztof Choromanski, Jake Varley, Honglak Lee, Jean-Jacques Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia, Vikas Sindhwani


  Access Paper or Ask Questions

Dimensions of Diversity in Human Perceptions of Algorithmic Fairness

May 02, 2020
Nina Grgińá-Hlańća, Adrian Weller, Elissa M. Redmiles

* Presented at the CSCW 2019 workshop on Team and Group Diversity 

  Access Paper or Ask Questions

Evaluating and Aggregating Feature-based Model Explanations

May 01, 2020
Umang Bhatt, Adrian Weller, José M. F. Moura

* Accepted at IJCAI 2020 

  Access Paper or Ask Questions

CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices

Apr 18, 2020
Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller


  Access Paper or Ask Questions

Stochastic Flows and Geometric Optimization on the Orthogonal Group

Mar 30, 2020
Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani


  Access Paper or Ask Questions

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision

Oct 31, 2019
Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti, Krishna P. Gummadi, Adrian Weller

* Accepted at NeurIPS 2019 HCML Workshop 

  Access Paper or Ask Questions

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning

Oct 30, 2019
Michiel A. Bakker, Duy Patrick Tu, Humberto Riverón Valdés, Krishna P. Gummadi, Kush R. Varshney, Adrian Weller, Alex Pentland

* Accepted at NeurIPS 2019 HCML Workshop 

  Access Paper or Ask Questions

Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks

Oct 09, 2019
Julius von K√ľgelgen, Paul K Rubenstein, Bernhard Sch√∂lkopf, Adrian Weller

* Working paper. Accepted as a poster at the NeurIPS 2019 workshop, "Do the right thing": machine learning and causal inference for improved decision making. (6 pages + references + appendix) 

  Access Paper or Ask Questions

Explainable Machine Learning in Deployment

Sep 13, 2019
Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley


  Access Paper or Ask Questions

The Sensitivity of Counterfactual Fairness to Unmeasured Confounding

Jul 01, 2019
Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva

* published at UAI 2019 

  Access Paper or Ask Questions

Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models

May 24, 2019
Yunfei Teng, Wenbo Gao, Francois Chalus, Anna Choromanska, Donald Goldfarb, Adrian Weller


  Access Paper or Ask Questions

Orthogonal Estimation of Wasserstein Distances

Apr 05, 2019
Mark Rowland, Jiri Hron, Yunhao Tang, Krzysztof Choromanski, Tamas Sarlos, Adrian Weller

* Published at AISTATS 2019 

  Access Paper or Ask Questions

The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings

Sep 03, 2018
Krzysztof Choromanski, Mark Rowland, Adrian Weller


  Access Paper or Ask Questions

Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018)

Jul 03, 2018
Been Kim, Kush R. Varshney, Adrian Weller


  Access Paper or Ask Questions

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Jul 02, 2018
Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar

* 12 pages 7 figures To be published in: KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Proceedings 

  Access Paper or Ask Questions

Structured Evolution with Compact Architectures for Scalable Policy Optimization

Jun 12, 2018
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller


  Access Paper or Ask Questions

Blind Justice: Fairness with Encrypted Sensitive Attributes

Jun 08, 2018
Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller

* Proceedings of the 35th International Conference on Machine Learning, PMLR 80:2630-2639, 2018 
* published at ICML 2018 

  Access Paper or Ask Questions

Bucket Renormalization for Approximate Inference

Mar 20, 2018
Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin


  Access Paper or Ask Questions

Gauged Mini-Bucket Elimination for Approximate Inference

Mar 04, 2018
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin, Adrian Weller


  Access Paper or Ask Questions

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction

Feb 26, 2018
Nina Grgińá-Hlańća, Elissa M. Redmiles, Krishna P. Gummadi, Adrian Weller

* To appear in the Proceedings of the Web Conference (WWW 2018). Code available at https://fate-computing.mpi-sws.org/procedural_fairness/ 

  Access Paper or Ask Questions