Zachary C. Lipton

Alex John London

Commun. ACM, May, 2024

Resolving the Human-subjects Status of Machine Learning's Crowdworkers: What ethical framework should govern the interaction of ML researchers and crowdworkers?

[BibT_eX]

[DOI]

Alex John London

ACM Queue, 2024

A Unified Causal Framework for Auditing Recommender Systems for Ethical Concerns.

[BibT_eX]

[DOI]

CoRR, 2024

LLM-Select: Feature Selection with Large Language Models.

[BibT_eX]

[DOI]

Daniel P. Jeong

Pradeep Ravikumar

CoRR, 2024

Understanding Hallucinations in Diffusion Models through Mode Interpolation.

[BibT_eX]

[DOI]

CoRR, 2024

Towards Bidirectional Human-AI Alignment: A Systematic Review for Clarifications, Framework, and Future Directions.

[BibT_eX]

[DOI]

CoRR, 2024

Rethinking LLM Memorization through the Lens of Adversarial Compression.

[BibT_eX]

[DOI]

CoRR, 2024

Post-Hoc Reversal: Are We Selecting Models Prematurely?

[BibT_eX]

[DOI]

CoRR, 2024

GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence.

[BibT_eX]

[DOI]

CoRR, 2024

Beyond the Mud: Datasets and Benchmarks for Computer Vision in Off-Road Racing.

[BibT_eX]

[DOI]

CoRR, 2024

Contrastive Multiple Instance Learning for Weakly Supervised Person ReID.

[BibT_eX]

[DOI]

CoRR, 2024

Personalized Language Modeling from Personalized Human Feedback.

[BibT_eX]

[DOI]

Xinyu Li

CoRR, 2024

Red-Teaming for Generative AI: Silver Bullet or Security Theater?

[BibT_eX]

[DOI]

CoRR, 2024

TOFU: A Task of Fictitious Unlearning for LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

Foundations of Testing for Finite-Sample Causal Discovery.

[BibT_eX]

[DOI]

Tom Yan

Ziyu Xu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Time-Varying Propensity Score to Bridge the Gap between the Past and Present.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Impact of Differential Feature Under-reporting on Algorithmic Fairness.

[BibT_eX]

[DOI]

Nil-Jana Akpinar

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains.

[BibT_eX]

[DOI]

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

Goodhart's Law Applies to NLP's Explanation Benchmarks.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

Scaling Laws for Data Filtering - Data Curation Cannot be Compute Agnostic.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

The Future of Web Data Mining: Insights from Multimodal and Code-based Extraction Methods.

[BibT_eX]

[DOI]

Evan Fellman

Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, 2024

Partially Interpretable Models with Guarantees on Coverage and Accuracy.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

Timing as an Action: Learning When to Observe and Act.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Auditing Fairness under Unobserved Confounding.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Analyzing LLM Behavior in Dialogue Summarization: Unveiling Circumstantial Hallucination Trends.

[BibT_eX]

[DOI]

Sanjana Ramprasad

Elisa Ferracane

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Perspectives on the State and Future of Deep Learning - 2023.

[BibT_eX]

[DOI]

CoRR, 2023

MoCo-Transfer: Investigating out-of-distribution contrastive learning for limited-data domains.

[BibT_eX]

[DOI]

Yuwen Chen

CoRR, 2023

Reading Between the Mud: A Challenging Motorcycle Racer Number Dataset.

[BibT_eX]

[DOI]

CoRR, 2023

MUDD: A New Re-Identification Dataset with Efficient Annotation for Off-Road Racers in Extreme Conditions.

[BibT_eX]

[DOI]

CoRR, 2023

PromptNER: Prompting For Named Entity Recognition.

[BibT_eX]

[DOI]

Dhananjay Ashok

CoRR, 2023

Users are the North Star for AI Transparency.

[BibT_eX]

[DOI]

CoRR, 2023

Discovering Optimal Scoring Mechanisms in Causal Strategic Prediction.

[BibT_eX]

[DOI]

Tom Yan

CoRR, 2023

Meta-Learning Mini-Batch Risk Functionals.

[BibT_eX]

[DOI]

CoRR, 2023

Risk-limiting financial audits via weighted sampling without replacement.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Deep Equilibrium Based Neural Operators for Steady-State PDEs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.

[BibT_eX]

[DOI]

Amrith Setlur

Virginia Smith

Aditi Raghunathan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms.

[BibT_eX]

[DOI]

Dheeraj Baby

Tzu-Ching Yen

Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reliable deep learning in dynamic environments.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Valla: Standardizing and Benchmarking Authorship Attribution and Verification Through Empirical Evaluation and Comparative Analysis.

[BibT_eX]

[DOI]

Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2023

CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Can Neural Network Memorization Be Localized?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

RLSbench: Domain Adaptation Under Relaxed Label Shift.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Disentangling the Mechanisms Behind Implicit Regularization in SGD.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DeepDrake ft. BTS-GAN and TayloRVC: An Exploratory Analysis of Musical Deepfakes and Hosting Platforms.

[BibT_eX]

[DOI]

Michael Feffer

Chris Donahue

Proceedings of the 2nd Workshop on Human-Centric Music Information Retrieval 2023 co-located with the 24th International Society for Music Information Retrieval Conference (ISMIR 2023), 2023

Model-tuning Via Prompts Makes NLP Models Adversarially Robust.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

USB: A Unified Summarization Benchmark Across Tasks and Domains.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Local Causal Discovery for Estimating Causal Effects.

[BibT_eX]

[DOI]

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Evaluating Model Performance in Medical Datasets Over Time.

[BibT_eX]

[DOI]

Yuwen Chen

Proceedings of the Conference on Health, Inference, and Learning, 2023

A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits.

[BibT_eX]

[DOI]

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

Domain Adaptation under Missingness Shift.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

From Preference Elicitation to Participatory ML: A Critical Survey & Guidelines for Future Research.

[BibT_eX]

[DOI]

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Downstream Datasets Make Surprisingly Good Pretraining Corpora.

[BibT_eX]

[DOI]

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Moral Machine or Tyranny of the Majority?

[BibT_eX]

[DOI]

Michael Feffer

Hoda Heidari

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?

[BibT_eX]

[DOI]

Trans. Assoc. Comput. Linguistics, 2022

Model Evaluation in Medical Datasets Over Time.

[BibT_eX]

[DOI]

Yuwen Chen

CoRR, 2022

Data drift correction via time-varying importance weight estimator.

[BibT_eX]

[DOI]

CoRR, 2022

On the State of the Art in Authorship Attribution and Authorship Verification.

[BibT_eX]

[DOI]

CoRR, 2022

Resolving the Human Subjects Status of Machine Learning's Crowdworkers.

[BibT_eX]

[DOI]

Alex John London

CoRR, 2022

Can Transformers be Strong Treatment Effect Estimators?

[BibT_eX]

[DOI]

CoRR, 2022

Unsupervised Learning under Latent Label Shift.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Characterizing Datapoints via Second-Split Forgetting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Domain Adaptation under Open Set Label Shift.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supervised Learning with General Risk Functionals.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Leveraging unlabeled data to predict out-of-distribution performance.

[BibT_eX]

[DOI]

Behnam Neyshabur

Hanie Sedghi

Proceedings of the Tenth International Conference on Learning Representations, 2022

On the Maximum Hessian Eigenvalue and Generalization.

[BibT_eX]

[DOI]

Simran Kaur

Jeremy Cohen

Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

Homophily and Incentive Effects in Use of Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Practical Benefits of Feature Feedback Under Distribution Shift.

[BibT_eX]

[DOI]

Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2022

Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2022, 2022

Off-Policy Risk Assessment for Markov Decision Processes.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Modeling Attrition in Recommender Systems with Departing Bandits.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

When Curation Becomes Creation: Algorithms, microcontent, and the vanishing distinction between platforms and creators.

[BibT_eX]

[DOI]

Dylan Hadfield-Menell

ACM Queue, 2021

The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies.

[BibT_eX]

[DOI]

Riccardo Fogliato

Proc. ACM Hum. Comput. Interact., 2021

Dive into Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2021

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk.

[BibT_eX]

[DOI]

CoRR, 2021

When curation becomes creation.

[BibT_eX]

[DOI]

Dylan Hadfield-Menell

Commun. ACM, 2021

Estimating treatment effects with observed confounders and mediators.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Parametric Complexity Bounds for Approximating PDEs with Neural Networks.

[BibT_eX]

[DOI]

Tanya Marwah

Andrej Risteski

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rebounding Bandits for Modeling Satiation Effects.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Off-Policy Risk Assessment in Contextual Bandits.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Online Estimation of Causal Effects by Deciding What to Observe.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Mixture Proportion Estimation and PU Learning: A Modern Approach.

[BibT_eX]

[DOI]

Yifan Wu

Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Correcting Exposure Bias for Link Recommendation.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

On Proximal Policy Optimization's Heavy-tailed Gradients.

[BibT_eX]

[DOI]

Ruslan Salakhutdinov

Pradeep Ravikumar

Proceedings of the 38th International Conference on Machine Learning, 2021

RATT: Leveraging Unlabeled Data to Guarantee Generalization.

[BibT_eX]

[DOI]

J. Zico Kolter

Proceedings of the 38th International Conference on Machine Learning, 2021

Explaining the Efficacy of Counterfactually Augmented Data.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data.

[BibT_eX]

[DOI]

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Does Pretraining for Summarization Require Knowledge Transfer?

[BibT_eX]

[DOI]

Kundan Krishna

Jeffrey P. Bigham

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Siamese Bert for Authorship Verification.

[BibT_eX]

[DOI]

Proceedings of the Working Notes of CLEF 2021 - Conference and Labs of the Evaluation Forum, Bucharest, Romania, September 21st - to, 2021

Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Causal Inference with Selectively Deconfounded Data.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes.

[BibT_eX]

[DOI]

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Fair Machine Learning Under Partial Compliance.

[BibT_eX]

[DOI]

Jessica Dai

Sina Fazelpour

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques.

[BibT_eX]

[DOI]

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study.

[BibT_eX]

[DOI]

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Symbolic Music Generation with Transformer-GANs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Tensor Regression Networks.

[BibT_eX]

[DOI]

Jean Kossaifi

Arinbjörn Kolbeinsson

Aran Khanna

Tommaso Furlanello

Anima Anandkumar

J. Mach. Learn. Res., 2020

Evaluating Explanations: How much do explanations from the teacher aid students?

[BibT_eX]

[DOI]

CoRR, 2020

Decoding and Diversity in Machine Translation.

[BibT_eX]

[DOI]

CoRR, 2020

Extracting Structured Data from Physician-Patient Conversations By Predicting Noteworthy Utterances.

[BibT_eX]

[DOI]

CoRR, 2020

Predicting Mortality Risk in Viral and Unspecified Pneumonia to Assist Clinicians with COVID-19 ECMO Planning.

[BibT_eX]

[DOI]

CoRR, 2020

Generating SOAP Notes from Doctor-Patient Conversations.

[BibT_eX]

[DOI]

CoRR, 2020

How Transferable are the Representations Learned by Deep Q Agents?

[BibT_eX]

[DOI]

CoRR, 2020

Machine Learning for Healthcare: Beyond i.i.d. Prediction.

[BibT_eX]

[DOI]

Proceedings of the ACM WSDM 2020 Health Search and Data Mining Workshop, 2020

SIGMOD 2020 Tutorial on Fairness and Bias in Peer Review and Other Sociotechnical Intelligent Systems.

[BibT_eX]

[DOI]

Nihar B. Shah

Proceedings of the 2020 International Conference on Management of Data, 2020

A Unified View of Label Shift Estimation.

[BibT_eX]

[DOI]

Yifan Wu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Uncertainty-Aware Lookahead Factor Models for Quantitative Investing.

[BibT_eX]

[DOI]

Lakshay Chauhan

John Alberg

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning The Difference That Makes A Difference With Counterfactually-Augmented Data.

[BibT_eX]

[DOI]

Eduard H. Hovy

Proceedings of the 8th International Conference on Learning Representations, 2020

Efficient Candidate Screening Under Multiple Tests and Implications for Fairness.

[BibT_eX]

[DOI]

Lee Cohen

Yishay Mansour

Proceedings of the 1st Symposium on Foundations of Responsible Computing, 2020

On Negative Interference in Multilingual Models: Findings and A Meta-Learning Treatment.

[BibT_eX]

[DOI]

Zirui Wang

Yulia Tsvetkov

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Weakly- and Semi-supervised Evidence Extraction.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Mortality Risk Score for Critically Ill Patients with Viral or Unspecified Pneumonia: Assisting Clinicians with COVID-19 ECMO Planning.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence in Medicine, 2020

Algorithmic Fairness from a Non-ideal Perspective.

[BibT_eX]

[DOI]

Sina Fazelpour

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

Learning to Deceive with Attention-Based Explanations.

[BibT_eX]

[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Troubling Trends in Machine Learning Scholarship.

[BibT_eX]

[DOI]

Jacob Steinhardt

ACM Queue, 2019

Are Perceptually-Aligned Gradients a General Property of Robust Classifiers?

[BibT_eX]

[DOI]

Simran Kaur

Jeremy Cohen

CoRR, 2019

Accelerating Deep Learning by Focusing on the Biggest Losers.

[BibT_eX]

[DOI]

CoRR, 2019

Estimating brain age based on a healthy population with deep learning and structural MRI.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Causal State Representations of Partially Observable Environments.

[BibT_eX]

[DOI]

Amy Zhang

Luis Pineda

CoRR, 2019

Temporal-Clustering Invariance in Irregular Healthcare Time Series.

[BibT_eX]

[DOI]

Mohammad Taha Bahadori

CoRR, 2019

Research for practice: troubling trends in machine-learning scholarship.

[BibT_eX]

[DOI]

Jacob Steinhardt

Commun. ACM, 2019

Game Design for Eliciting Distinguishable Behavior.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Robust Global Representations by Penalizing Local Predictive Power.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift.

[BibT_eX]

[DOI]

Stephan Rabanser

Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Healthcare Conference, 2019

AmazonQA: A Review-Based Question Answering Task.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

What is the Effect of Importance Weighting in Deep Learning?

[BibT_eX]

[DOI]

Jonathon Byrd

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Robust Representations by Projecting Superficial Statistics Out.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Active Learning with Partial Feedback.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Practical Obstacles to Deploying Active Learning.

[BibT_eX]

[DOI]

David Lowell

Byron C. Wallace

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Entity Projection via Machine Translation for Cross-Lingual NER.

[BibT_eX]

[DOI]

Alankar Jain

Bhargavi Paranjape

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Combating Adversarial Misspellings with Robust Word Recognition.

[BibT_eX]

[DOI]

Danish Pruthi

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

The Mythos of Model Interpretability.

[BibT_eX]

[DOI]

ACM Queue, 2018

Weighted Risk Minimization & Deep Learning.

[BibT_eX]

[DOI]

Jonathon Byrd

CoRR, 2018

How transferable are the datasets collected by active learners?

[BibT_eX]

[DOI]

David Lowell

Byron C. Wallace

CoRR, 2018

Sample-Efficient Deep RL with Generative Adversarial Tree Search.

[BibT_eX]

[DOI]

CoRR, 2018

Correction by Projection: Denoising Images with Generative Adversarial Networks.

[BibT_eX]

[DOI]

Subarna Tripathi

Truong Q. Nguyen

CoRR, 2018

Learning Noise-Invariant Representations for Robust Speech Recognition.

[BibT_eX]

[DOI]

Davis Liang

Zhiheng Huang

Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018

Does mitigating ML's impact disparity require treatment disparity?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Detecting and Correcting for Label Shift with Black Box Predictors.

[BibT_eX]

[DOI]

Yu-Xiang Wang

Alexander J. Smola

Proceedings of the 35th International Conference on Machine Learning, 2018

Born-Again Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Predicting Embryo Morphokinetics in Videos with Late Fusion Nets & Dynamic Decoders.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning From Noisy Singly-labeled Data.

[BibT_eX]

[DOI]

Ashish Khetan

Proceedings of the 6th International Conference on Learning Representations, 2018

Semantically Decomposing the Latent Spaces of Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Stochastic Activation Pruning for Robust Adversarial Defense.

[BibT_eX]

[DOI]

Guneet S. Dhillon

Proceedings of the 6th International Conference on Learning Representations, 2018

Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study.

[BibT_eX]

[DOI]

Aditya Siddhant

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks.

[BibT_eX]

[DOI]

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Learning from Temporally-Structured Human Activities Data.

[BibT_eX]

[DOI]

PhD thesis, 2017

Does mitigating ML's disparate impact require disparate treatment?

[BibT_eX]

[DOI]

CoRR, 2017

Improving Factor-Based Quantitative Investing by Forecasting Company Fundamentals.

[BibT_eX]

[DOI]

John Alberg

CoRR, 2017

Tensor Regression Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Deep Active Learning for Named Entity Recognition.

[BibT_eX]

[DOI]

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Predicting Surgery Duration with Neural Heteroscedastic Regression.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Health Care Conference, 2017

Estimating Reactions and Recommending Products with Generative Models of Reviews.

[BibT_eX]

[DOI]

Proceedings of the Eighth International Joint Conference on Natural Language Processing, 2017

Dance Dance Convolution.

[BibT_eX]

[DOI]

Chris Donahue

Proceedings of the 34th International Conference on Machine Learning, 2017

Precise Recovery of Latent Vectors from Generative Adversarial Networks.

[BibT_eX]

[DOI]

Subarna Tripathi

Proceedings of the 5th International Conference on Learning Representations, 2017

Tensor Contraction Layers for Parsimonious Deep Nets.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

2016

Learning to Diagnose with LSTM Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Efficient Exploration for Dialog Policy Learning with Deep BBQ Networks \& Replay Buffer Spiking.

[BibT_eX]

[DOI]

CoRR, 2016

Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear.

[BibT_eX]

[DOI]

CoRR, 2016

Stuck in a What? Adventures in Weight Space.

[BibT_eX]

[DOI]

CoRR, 2016

A User Simulator for Task-Completion Dialogues.

[BibT_eX]

[DOI]

CoRR, 2016

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series.

[BibT_eX]

[DOI]

David C. Kale

Randall C. Wetzel

Proceedings of the 1st Machine Learning in Health Care, 2016

Context Matters: Refining Object Detection in Video with Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2016, 2016

2015

Capturing Meaning in Product Reviews with Character-Level Generative Text Models.

[BibT_eX]

[DOI]

Sharad Vikram

CoRR, 2015

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks.

[BibT_eX]

[DOI]

David C. Kale

Randall C. Wetzel

CoRR, 2015

Efficient Elastic Net Regularization for Sparse Linear Models.

[BibT_eX]

[DOI]

CoRR, 2015

A Critical Review of Recurrent Neural Networks for Sequence Learning.

[BibT_eX]

[DOI]

CoRR, 2015

2014

F1-Optimal Thresholding in the Multi-Label Setting.

[BibT_eX]

[DOI]

Balakrishnan Narayanaswamy

CoRR, 2014

Differential Privacy and Machine Learning: a Survey and Review.

[BibT_eX]

[DOI]

Zhanglong Ji

CoRR, 2014

Optimal Thresholding of Classifiers to Maximize F1 Measure.

[BibT_eX]

[DOI]