| 2026 | COLT | Linear Regression under Missing or Corrupted Coordinates. | Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas |
| 2026 | COLT | A Quasi-Polynomial Time Mean Estimator Under Mean-Shift Contamination with Unknown Covariance. | Ilias Diakonikolas, Jingyi Gao, Giannis Iakovidis, Daniel M. Kane, Sihan Liu, Thanasis Pittas |
| 2026 | COLT | High-Dimensional Gaussian Mean Estimation under Realizable Contamination. | Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas |
| 2026 | STOC | High-Accuracy List-Decodable Mean Estimation. | Ziyun Chen, Spencer Compton, Daniel M. Kane, Jerry Li |
| 2026 | STOC | Rigorous Implications of the Low-Degree Heuristic. | Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari, Jerry Li, Sidhanth Mohanty, Stefan Tiegel |
| 2025 | ALT | Do PAC-Learners Learn the Marginal Distribution? | Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan |
| 2025 | COLT | Faster Algorithms for Agnostically Learning Disjunctions and their Implications. | Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren |
| 2025 | FOCS | Robust Learning of Multi-index Models via Iterative Subspace Approximation. | Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Nikos Zarifis |
| 2025 | FOCS | Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models. | Ilias Diakonikolas, Daniel M. Kane |
| 2025 | FOCS | PTF Testing Lower Bounds for Non-Gaussian Component Analysis. | Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Thanasis Pittas |
| 2025 | SODA | Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation. | Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas |
| 2025 | STOC | Entangled Mean Estimation in High Dimensions. | Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Thanasis Pittas |
| 2025 | STOC | Locally Sampleable Uniform Symmetric Distributions. | Daniel M. Kane, Anthony Ostuni, Kewen Wu |
| 2024 | COLT | New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions. | Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng |
| 2024 | COLT | Efficiently Learning One-Hidden-Layer ReLU Networks via SchurPolynomials. | Ilias Diakonikolas, Daniel M. Kane |
| 2024 | COLT | Testable Learning of General Halfspaces with Adversarial Label Noise. | Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Nikos Zarifis |
| 2024 | COLT | Statistical Query Lower Bounds for Learning Truncated Gaussians. | Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis |
| 2024 | FOCS | Agnostically Learning Multi-Index Models with Queries. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis |
| 2024 | FOCS | Replicability in High Dimensional Statistics. | Max Hopkins, Russell Impagliazzo, Daniel M. Kane, Sihan Liu, Christopher Ye |
| 2024 | SODA | Online Robust Mean Estimation. | Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu |
| 2024 | STOC | Super Non-singular Decompositions of Polynomials and Their Application to Robustly Learning Low-Degree PTFs. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis |
| 2024 | STOC | Testing Closeness of Multivariate Distributions via Ramsey Theory. | Ilias Diakonikolas, Daniel M. Kane, Sihan Liu |
| 2024 | STOC | Locality Bounds for Sampling Hamming Slices. | Daniel M. Kane, Anthony Ostuni, Kewen Wu |
| 2023 | COLT | Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. | Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis |
| 2023 | COLT | Statistical and Computational Limits for Tensor-on-Tensor Association Detection. | Ilias Diakonikolas, Daniel M. Kane, Yuetian Luo, Anru Zhang |
| 2023 | COLT | SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians. | Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis |
| 2023 | STOC | A Strongly Polynomial Algorithm for Approximate Forster Transforms and Its Application to Halfspace Learning. | Ilias Diakonikolas, Christos Tzamos, Daniel M. Kane |
| 2022 | AISTATS | Coresets for Data Discretization and Sine Wave Fitting. | Alaa Maalouf, Murad Tukan, Eric Price, Daniel M. Kane, Dan Feldman |
| 2022 | COLT | Robust Sparse Mean Estimation via Sum of Squares. | Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas |
| 2022 | COLT | Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models. | Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun |
| 2022 | COLT | Realizable Learning is All You Need. | Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan |
| 2022 | ICML | Streaming Algorithms for High-Dimensional Robust Statistics. | Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas |
| 2022 | STOC | Robustly learning mixtures of | Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala |
| 2022 | STOC | Clustering mixture models in almost-linear time via list-decodable mean estimation. | Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian |
| 2022 | STOC | Learning general halfspaces with general Massart noise under the Gaussian distribution. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis |
| 2021 | COLT | Boosting in the Presence of Massart Noise. | Ilias Diakonikolas, Russell Impagliazzo, Daniel M. Kane, Rex Lei, Jessica Sorrell, Christos Tzamos |
| 2021 | COLT | The Sample Complexity of Robust Covariance Testing. | Ilias Diakonikolas, Daniel M. Kane |
| 2021 | COLT | Agnostic Proper Learning of Halfspaces under Gaussian Marginals. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis |
| 2021 | COLT | The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model. | Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis |
| 2021 | COLT | Outlier-Robust Learning of Ising Models Under Dobrushin's Condition. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun |
| 2021 | SODA | Robust Learning of Mixtures of Gaussians. | Daniel M. Kane |
| 2021 | STOC | Optimal testing of discrete distributions with high probability. | Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price |
| 2021 | STOC | Efficiently learning halfspaces with Tsybakov noise. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis |
| 2020 | COLT | Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks. | Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Nikos Zarifis |
| 2020 | FOCS | Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models. | Ilias Diakonikolas, Daniel M. Kane |
| 2019 | COLT | Communication and Memory Efficient Testing of Discrete Distributions. | Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, Sankeerth Rao |
| 2019 | COLT | Testing Identity of Multidimensional Histograms. | Ilias Diakonikolas, Daniel M. Kane, John Peebles |
| 2019 | COLT | Learning Ising Models with Independent Failures. | Surbhi Goel, Daniel M. Kane, Adam R. Klivans |
| 2019 | STOC | Degree-푑 chow parameters robustly determine degree-푑 PTFs (and algorithmic applications). | Ilias Diakonikolas, Daniel M. Kane |
| 2018 | ICALP | Generalized Comparison Trees for Point-Location Problems. | Daniel M. Kane, Shachar Lovett, Shay Moran |
| 2018 | ITA | Testing Conditional Independence of Discrete Distributions. | Clment L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2018 | SODA | Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. | Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart |
| 2018 | STOC | Testing conditional independence of discrete distributions. | Clment L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2018 | STOC | List-decodable robust mean estimation and learning mixtures of spherical gaussians. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2018 | STOC | Learning geometric concepts with nasty noise. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2018 | STOC | Near-optimal linear decision trees for k-SUM and related problems. | Daniel M. Kane, Shachar Lovett, Shay Moran |
| 2017 | COLT | Testing Bayesian Networks. | Clment L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2017 | COLT | Learning Multivariate Log-concave Distributions. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2017 | FOCS | Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2017 | FOCS | Active Classification with Comparison Queries. | Daniel M. Kane, Shachar Lovett, Shay Moran, Jiapeng Zhang |
| 2017 | ICALP | Near-Optimal Closeness Testing of Discrete Histogram Distributions. | Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin |
| 2017 | ICML | Being Robust (in High Dimensions) Can Be Practical. | Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart |
| 2017 | STOC | A polynomial restriction lemma with applications. | Valentine Kabanets, Daniel M. Kane, Zhenjian Lu |
| 2016 | COLT | Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2016 | COLT | Properly Learning Poisson Binomial Distributions in Almost Polynomial Time. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2016 | FOCS | Fourier-Sparse Interpolation without a Frequency Gap. | Xue Chen, Daniel M. Kane, Eric Price, Zhao Song |
| 2016 | FOCS | A New Approach for Testing Properties of Discrete Distributions. | Ilias Diakonikolas, Daniel M. Kane |
| 2016 | FOCS | Robust Estimators in High Dimensions without the Computational Intractability. | Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart |
| 2016 | STOC | The fourier transform of poisson multinomial distributions and its algorithmic applications. | Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart |
| 2016 | STOC | Super-linear gate and super-quadratic wire lower bounds for depth-two and depth-three threshold circuits. | Daniel M. Kane, Ryan Williams |
| 2015 | FOCS | Optimal Algorithms and Lower Bounds for Testing Closeness of Structured Distributions. | Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin |
| 2015 | FOCS | Pseudorandomness via the Discrete Fourier Transform. | Parikshit Gopalan, Daniel M. Kane, Raghu Meka |
| 2015 | SODA | Testing Identity of Structured Distributions. | Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin |
| 2014 | ISAAC | A Short Implicant of a CNF Formula with Many Satisfying Assignments. | Daniel M. Kane, Osamu Watanabe |
| 2014 | STOC | The average sensitivity of an intersection of half spaces. | Daniel M. Kane |
| 2013 | COLT | Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching. | Daniel M. Kane, Adam R. Klivans, Raghu Meka |
| 2013 | STOC | A PRG for lipschitz functions of polynomials with applications to sparsest cut. | Daniel M. Kane, Raghu Meka |
| 2012 | FOCS | A Structure Theorem for Poorly Anticoncentrated Gaussian Chaoses and Applications to the Study of Polynomial Threshold Functions. | Daniel M. Kane |
| 2012 | ICALP | Counting Arbitrary Subgraphs in Data Streams. | Daniel M. Kane, Kurt Mehlhorn, Thomas Sauerwald, He Sun |
| 2012 | SODA | Sparser Johnson-Lindenstrauss transforms. | Daniel M. Kane, Jelani Nelson |
| 2011 | FOCS | A Small PRG for Polynomial Threshold Functions of Gaussians. | Daniel M. Kane |
| 2011 | STOC | Fast moment estimation in data streams in optimal space. | Daniel M. Kane, Jelani Nelson, Ely Porat, David P. Woodruff |
| 2010 | FOCS | Bounded Independence Fools Degree-2 Threshold Functions. | Ilias Diakonikolas, Daniel M. Kane, Jelani Nelson |
| 2010 | PODS | An optimal algorithm for the distinct elements problem. | Daniel M. Kane, Jelani Nelson, David P. Woodruff |
| 2010 | SODA | On the Exact Space Complexity of Sketching and Streaming Small Norms. | Daniel M. Kane, Jelani Nelson, David P. Woodruff |