Review quality aware collaborative filtering. - Sindhu Raghavan; Suriya Gunasekar; Joydeep Ghosh (RecSys, 2012)

Noisy Matrix Completion Using Alternating Minimization. - Suriya Gunasekar; Ayan Acharya; Neeraj Gaur; Joydeep Ghosh (ECML/PKDD (2), 2013)

Face detection on distorted images using perceptual quality-aware features. - Suriya Gunasekar; Joydeep Ghosh; Alan C. Bovik (Human Vision and Electronic Imaging, 2014)

Exponential Family Matrix Completion under Structural Constraints. - Suriya Gunasekar; Pradeep Ravikumar; Joydeep Ghosh (ICML, 2014)

Face Detection on Distorted Images Augmented by Perceptual Quality-Aware Features. - Suriya Gunasekar; Joydeep Ghosh; Alan C. Bovik (IEEE Trans. Inf. Forensics Secur., 2014)

Consistent Collective Matrix Completion under Joint Low Rank Structure. - Suriya Gunasekar; Makoto Yamada; Dawei Yin; Yi Chang 001 (AISTATS, 2015)

Unified View of Matrix Completion under General Structural Constraints. - Suriya Gunasekar; Arindam Banerjee 001; Joydeep Ghosh (NIPS, 2015)

Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. - Shalmali Joshi; Suriya Gunasekar; David A. Sontag; Joydeep Ghosh (MLHC, 2016)

Preference Completion from Partial Rankings. - Suriya Gunasekar; Oluwasanmi Koyejo; Joydeep Ghosh (NIPS, 2016)

Learning Non-Discriminatory Predictors. - Blake E. Woodworth; Suriya Gunasekar; Mesrob I. Ohannessian; Nathan Srebro (COLT, 2017)

Implicit Regularization in Matrix Factorization. - Suriya Gunasekar; Blake E. Woodworth; Srinadh Bhojanapalli; Behnam Neyshabur; Nati Srebro (NIPS, 2017)

Characterizing Implicit Bias in Terms of Optimization Geometry. - Suriya Gunasekar; Jason D. Lee; Daniel Soudry; Nathan Srebro (ICML, 2018)

On preserving non-discrimination when combining expert advice. - Avrim Blum; Suriya Gunasekar; Thodoris Lykouris; Nati Srebro (NeurIPS, 2018)

Implicit Bias of Gradient Descent on Linear Convolutional Networks. - Suriya Gunasekar; Jason D. Lee; Daniel Soudry; Nati Srebro (NeurIPS, 2018)

Convergence of Gradient Descent on Separable Data. - Mor Shpigel Nacson; Jason D. Lee; Suriya Gunasekar; Nathan Srebro; Daniel Soudry (CoRR, 2018)

The Implicit Bias of Gradient Descent on Separable Data. - Daniel Soudry; Elad Hoffer; Mor Shpigel Nacson; Suriya Gunasekar; Nathan Srebro (J. Mach. Learn. Res., 2018)

Convergence of Gradient Descent on Separable Data. - Mor Shpigel Nacson; Jason D. Lee; Suriya Gunasekar; Pedro Henrique Pamplona Savarese; Nathan Srebro; Daniel Soudry (AISTATS, 2019)

Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models. - Mor Shpigel Nacson; Suriya Gunasekar; Jason D. Lee; Nathan Srebro; Daniel Soudry (ICML, 2019)

Implicit Regularization of Normalization Methods. - Xiaoxia Wu; Edgar Dobriban; Tongzheng Ren; Shanshan Wu; Zhiyuan Li; Suriya Gunasekar; Rachel A. Ward; Qiang Liu 001 (CoRR, 2019)

Kernel and Rich Regimes in Overparametrized Models. - Blake E. Woodworth; Suriya Gunasekar; Jason D. Lee; Edward Moroshko; Pedro Savarese; Itay Golan; Daniel Soudry; Nathan Srebro (COLT, 2020)

Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. - Yiding Jiang; Parth Natekar; Manik Sharma; Sumukh K. Aithal; Dhruva Kashyap; Natarajan Subramanyam; Carlos Lassance; Daniel M. Roy 001; Gintare Karolina Dziugaite; Suriya Gunasekar; Isabelle Guyon; Pierre Foret; et al. (NeurIPS (Competition and Demos), 2020)

Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy. - Edward Moroshko; Blake E. Woodworth; Suriya Gunasekar; Jason D. Lee; Nati Srebro; Daniel Soudry (NeurIPS, 2020)

Implicit Regularization and Convergence for Weight Normalization. - Xiaoxia Wu; Edgar Dobriban; Tongzheng Ren; Shanshan Wu; Zhiyuan Li; Suriya Gunasekar; Rachel A. Ward; Qiang Liu 001 (NeurIPS, 2020)

Mirrorless Mirror Descent: A More Natural Discretization of Riemannian Gradient Flow. - Suriya Gunasekar; Blake E. Woodworth; Nathan Srebro (CoRR, 2020)

NeurIPS 2020 Competition: Predicting Generalization in Deep Learning. - Yiding Jiang; Pierre Foret; Scott Yak; Daniel M. Roy 001; Hossein Mobahi; Gintare Karolina Dziugaite; Samy Bengio; Suriya Gunasekar; Isabelle Guyon; Behnam Neyshabur (CoRR, 2020)

Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent. - Suriya Gunasekar; Blake E. Woodworth; Nathan Srebro (AISTATS, 2021)

Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm. - Meena Jagadeesan; Ilya P. Razenshteyn; Suriya Gunasekar (COLT, 2022)

Neural-Sim: Learning to Generate Training Data with NeRF. - Yunhao Ge; Harkirat S. Behl; Jiashu Xu; Suriya Gunasekar; Neel Joshi; Yale Song; Xin Wang 066; Laurent Itti; Vibhav Vineet (ECCV (23), 2022)

Data Augmentation as Feature Manipulation. - Ruoqi Shen; Sébastien Bubeck; Suriya Gunasekar (ICML, 2022)

Data Augmentation as Feature Manipulation: a story of desert cows and grass cows. - Ruoqi Shen; Sébastien Bubeck; Suriya Gunasekar (CoRR, 2022)

Unveiling Transformers with LEGO: a synthetic reasoning task. - Yi Zhang; Arturs Backurs; Sébastien Bubeck; Ronen Eldan; Suriya Gunasekar; Tal Wagner (CoRR, 2022)

Generalization to translation shifts: a study in architectures and augmentations. - Suriya Gunasekar (CoRR, 2022)

(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability. - Mathieu Even; Scott Pesme; Suriya Gunasekar; Nicolas Flammarion (NeurIPS, 2023)

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability. - Mathieu Even; Scott Pesme; Suriya Gunasekar; Nicolas Flammarion (CoRR, 2023)

Textbooks Are All You Need. - Suriya Gunasekar; Yi Zhang 001; Jyoti Aneja; Caio César Teodoro Mendes; Allie Del Giorno; Sivakanth Gopi; Mojan Javaheripi; Piero Kauffmann; Gustavo de Rosa; Olli Saarikivi; Adil Salim; Shital Shah; et al. (CoRR, 2023)

Textbooks Are All You Need II: phi-1.5 technical report. - Yuanzhi Li; Sébastien Bubeck; Ronen Eldan; Allie Del Giorno; Suriya Gunasekar; Yin Tat Lee (CoRR, 2023)

KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval. - Marah I Abdin; Suriya Gunasekar; Varun Chandrasekaran; Jerry Li; Mert Yüksekgönül; Rahee Ghosh Peshawaria; Ranjita Naik; Besmira Nushi (ICLR, 2024)

How to Fine-Tune Vision Models with SGD. - Ananya Kumar; Ruoqi Shen; Sébastien Bubeck; Suriya Gunasekar (ICLR, 2024)

Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models. - Mert Yüksekgönül; Varun Chandrasekaran; Erik Jones; Suriya Gunasekar; Ranjita Naik; Hamid Palangi; Ece Kamar; Besmira Nushi (ICLR, 2024)

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone. - Marah I Abdin; Sam Ade Jacobs; Ammar Ahmad Awan; Jyoti Aneja; Ahmed Awadallah 001; Hany Awadalla; Nguyen Bach; Amit Bahree; Arash Bakhtiari; Harkirat S. Behl; Alon Benhaim; Misha Bilenko; et al. (CoRR, 2024)

Phi-4 Technical Report. - Marah I Abdin; Jyoti Aneja; Harkirat S. Behl; Sébastien Bubeck; Ronen Eldan; Suriya Gunasekar; Michael Harrison; Russell J. Hewett; Mojan Javaheripi; Piero Kauffmann; James R. Lee; Yin Tat Lee; et al. (CoRR, 2024)

Phi-4-reasoning Technical Report. - Marah I Abdin; Sahaj Agarwal; Ahmed Awadallah 001; Vidhisha Balachandran; Harkirat S. Behl; Lingjiao Chen; Gustavo de Rosa; Suriya Gunasekar; Mojan Javaheripi; Neel Joshi; Piero Kauffmann; Yash Lara; et al. (CoRR, 2025)