Search Results - Risteski, Andrej

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  1. 1
    Linear Algebraic Structure of Word Senses, with Applications to Polysemy

    Linear Algebraic Structure of Word Senses, with Applications to Polysemy by Arora, Sanjeev, Li, Yuanzhi, Liang, Yingyu, Ma, Tengyu, Risteski, Andrej

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  2. 2
    A Latent Variable Model Approach to PMI-based Word Embeddings

    A Latent Variable Model Approach to PMI-based Word Embeddings by Arora, Sanjeev, Li, Yuanzhi, Liang, Yingyu, Ma, Tengyu, Risteski, Andrej

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  3. 3
    Skeletal configurations of ribbon trees

    Skeletal configurations of ribbon trees by Cheng, Howard, Devadoss, Satyan L., Li, Brian, Risteski, Andrej

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  4. 4
    Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Diffusions

    Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Diffusions by Qin, Yilong, Risteski, Andrej

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  5. 5
    Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization

    Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization by Rosenfeld, Elan, Risteski, Andrej

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  6. 6
    Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions

    Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions by Peng, Binghui, Risteski, Andrej

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  7. 7
    The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders

    The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders by Pareek, Divyansh, Risteski, Andrej

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  8. 8
    The Limitations of Limited Context for Constituency Parsing

    The Limitations of Limited Context for Constituency Parsing by Li, Yuchen, Risteski, Andrej

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  9. 9
    Fast Convergence for Langevin Diffusion with Manifold Structure

    Fast Convergence for Langevin Diffusion with Manifold Structure by Moitra, Ankur, Risteski, Andrej

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  10. 10
    How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding

    How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding by Li, Yuchen, Li, Yuanzhi, Risteski, Andrej

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  11. 11
    How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods

    How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods by Risteski, Andrej

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  12. 12
    Progressive distillation induces an implicit curriculum

    Progressive distillation induces an implicit curriculum by Panigrahi, Abhishek, Liu, Bingbin, Malladi, Sadhika, Risteski, Andrej, Goel, Surbhi

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  13. 13
    On the Benefits of Memory for Modeling Time-Dependent PDEs

    On the Benefits of Memory for Modeling Time-Dependent PDEs by Ricardo Buitrago Ruiz, Marwah, Tanya, Gu, Albert, Risteski, Andrej

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  14. 14
    Statistical Efficiency of Score Matching: The View from Isoperimetry

    Statistical Efficiency of Score Matching: The View from Isoperimetry by Koehler, Frederic, Heckett, Alexander, Risteski, Andrej

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  15. 15
    Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization

    Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization by Rosenfeld, Elan, Ravikumar, Pradeep, Risteski, Andrej

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  16. 16
    Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression

    Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression by Zhai, Runtian, Liu, Bingbin, Risteski, Andrej, Kolter, Zico, Ravikumar, Pradeep

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  17. 17
    Efficient sampling from the Bingham distribution

    Efficient sampling from the Bingham distribution by Ge, Rong, Holden, Lee, Lu, Jianfeng, Risteski, Andrej

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  18. 18
    Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars

    Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars by Wen, Kaiyue, Li, Yuchen, Liu, Bingbin, Risteski, Andrej

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  19. 19
    Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods

    Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods by Koehler, Frederic, Holden, Lee, Risteski, Andrej

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  20. 20
    An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization

    An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization by Rosenfeld, Elan, Ravikumar, Pradeep, Risteski, Andrej

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