Lang, Hunter

14 publications

ICML 2025 On the Duality Between Gradient Transformations and Adapters Lucas Torroba Hennigen, Hunter Lang, Han Guo, Yoon Kim

NeurIPS 2024 Theoretical Analysis of Weak-to-Strong Generalization Hunter Lang, David Sontag, Aravindan Vijayaraghavan

AISTATS 2023 TabLLM: Few-Shot Classification of Tabular Data with Large Language Models Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David Sontag

AISTATS 2023 Who Should Predict? Exact Algorithms for Learning to Defer to Humans Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David Sontag

AISTATS 2022 Leveraging Time Irreversibility with Order-Contrastive Pre-Training Monica N. Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David Sontag

ICML 2022 Co-Training Improves Prompt-Based Learning for Large Language Models Hunter Lang, Monica N Agrawal, Yoon Kim, David Sontag

NeurIPS 2022 Training Subset Selection for Weak Supervision Hunter Lang, Aravindan Vijayaraghavan, David Sontag

AISTATS 2021 Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances Hunter Lang, Aravind Reddy, David Sontag, Aravindan Vijayaraghavan

ICML 2021 Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch) Hunter Lang, David Sontag, Aravindan Vijayaraghavan

AAAI 2021 Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic Hunter Lang, Hoifung Poon

AISTATS 2019 Block Stability for MAP Inference Hunter Lang, David Sontag, Aravindan Vijayaraghavan

NeurIPS 2019 Understanding the Role of Momentum in Stochastic Gradient Methods Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao

NeurIPS 2019 Using Statistics to Automate Stochastic Optimization Hunter Lang, Lin Xiao, Pengchuan Zhang

AISTATS 2018 Optimality of Approximate Inference Algorithms on Stable Instances Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan