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Number of items: 27.
A
Aitchison, L;
Bang, D;
Bahrami, B;
Latham, PE;
(2015)
Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making.
PLoS Computational Biology
, 11
(10)
, Article e1004519. 10.1371/journal.pcbi.1004519.
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Jitkrittum, W;
Gretton, A;
Heess, N;
Eslami, A;
Lakshminarayanan, B;
Sejdinovic, D;
Szabo, Z;
(2015)
Just-In-Time Kernel Regression for Expectation Propagation.
In:
Proceeding of Large-Scale Kernel Learning: Challenges and New Opportunities workshop.
: Lille, France.
(In press).
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Jitkrittum, W;
Gretton, A;
Heess, N;
Eslami, A;
Lakshminarayanan, B;
Sejdinovic, D;
Szabo, Z;
(2015)
Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.
Presented at: Data, Learning and Inference workshop (DALI), La Palma (Canaries, Spain).
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Jitkrittum, W;
Gretton, A;
Heess, N;
Eslami, SMA;
Lakshminarayanan, B;
Sejdinovic, D;
Szabó, Z;
(2015)
Kernel-based just-in-time learning for passing expectation propagation messages.
In: Meila, Marina and Heskes, Tom, (eds.)
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence (UAI'15 ).
(pp. pp. 405-414).
AUAI Press: Virginia, USA.
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Jitkrittum, W;
Gretton, AL;
Heess, N;
Eslami, SMA;
Lakshminarayanan, B;
Sejdinovic, D;
Szabó, Z;
(2015)
Kernel-Based Just-In-Time Learning For Passing Expectation Propagation Messages.
Presented at: International Conference on Machine Learning (ICML) - Large-Scale Kernel Learning: Challenges and New Opportunities workshop, Lille, France.
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P
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Pachitariu, M;
Lyamzin, DR;
Sahani, M;
Lesica, NA;
(2015)
State-dependent population coding in primary auditory cortex.
J Neurosci
, 35
(5)
pp. 2058-2073.
10.1523/JNEUROSCI.3318-14.2015.
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Park, M;
Jitkrittum, W;
Qamar, A;
Szabo, Z;
Buesing, L;
Sahani, M;
(2015)
Bayesian Manifold Learning: Locally Linear Latent Variable Model (LL-LVM).
Presented at: Quinquennial Review Symposium, London, United Kingdom.
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Poort, J;
Khan, AG;
Pachitariu, M;
Nemri, A;
Orsolic, I;
Krupic, J;
Bauza, M;
... Hofer, SB; + view all
(2015)
Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex.
Neuron
, 86
(6)
pp. 1478-1490.
10.1016/j.neuron.2015.05.037.
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S
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Sriperumbudur, B;
Szabo, Z;
(2015)
Optimal Rates for Random Fourier Feature Approximations.
Presented at: Talk at University of Alberta, Edmonton, Alberta, Canada.
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Sriperumbudur, B;
Szabo, Z;
(2015)
Optimal Rates for Random Fourier Feature Kernel Approximations.
Presented at: Talk at UC Berkeley: AMPLab, Berkeley, California.
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Sriperumbudur, B;
Szabo, Z;
(2015)
Optimal Rates for Random Fourier Features.
Presented at: Neural Information Processing Systems (NIPS-2015), Montréal, Canada.
(In press).
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Sriperumbudur, B;
Szabo, Z;
(2015)
Optimal Uniform and Lp Rates for Random Fourier Features.
Presented at: Talk at Pennsylvania State University, Pennsylvania State University, USA.
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Sriperumbudur, B;
Szabo, Z;
(2015)
Optimal Uniform and Lp Rates for Random Fourier Features.
Presented at: Quinquennial Review Symposium, Gatsby Unit, London, Unite Kingdom.
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Sriperumbudur, B;
Szabo, Z;
(2015)
Performance Guarantees for Random Fourier Features - Limitations and Merits.
Presented at: ML@SITraN, University of Sheffield, Sheffield, Unite Kingdom.
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Strathmann, H;
Sejdinovic, D;
Livingstone, S;
Szabo, Z;
Gretton, A;
(2015)
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families.
In: Cortes, C and Lawrence, ND and Lee, DD and Sugiyama, M and Garnett, R, (eds.)
Advances in Neural Information Processing Systems 28 (NIPS 2015).
NIPS Proceedings
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Szabó, Z;
Sriperumbudur, BK;
(2015)
Optimal Rates for the Random Fourier Feature Method.
Presented at: Talk at Carnegie Mellon University: Statistical ML Reading Group, Pittsburgh, PA, USA.
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Szabo, Z;
Gretton, A;
Póczos, B;
Sriperumbudur, B;
(2015)
Consistent Vector-valued Distribution Regression.
Presented at: UCL Workshop on the Theory of Big Data, London, UK.
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Szabo, Z;
Gretton, A;
Poczos, B;
Sriperumbudur, B;
(2015)
Two-stage Sampled Learning Theory on Distributions.
In: Lebanon, G and Vishwanathan, SVN, (eds.)
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics.
(pp. pp. 948-957).
Journal of Machine Learning Research: San Diego, CA, USA.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Consistent Vector-valued Regression on Probability Measures.
Presented at: Invited talk at Prof. Bernhard Schölkopf's lab, Tübingen.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Distribution Regression - Make It Simple and Consistent.
Presented at: Data, Learning and Inference workshop (DALI), La Palma (Canaries, Spain).
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Distribution Regression: Computational and Statistical Tradeoffs.
Presented at: Talk at Princeton University, Princeton, New Jersey.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Distribution Regression: Computational and Statistical Tradeoffs.
Presented at: CSML Lunch Talk Series, London, United Kingdom.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Learning Theory for Vector-Valued Distribution Regression.
Presented at: CMStatistics 2015, London, United Kingdom.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Regression on Probability Measures: A Simple and Consistent Algorithm.
Presented at: CRiSM Seminars, Department of Statistics, University of Warwick, Coventry, United Kingdom.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
A Simple and Consistent Technique for Vector-valued Distribution Regression.
Presented at: Invited talk at the Artificial Intelligence and Natural Computation seminars, University of Birmingham, UK.
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Szabo, Z;
Sriperumbudur, B;
Poczos, B;
Gretton, A;
(2015)
Vector-valued Distribution Regression - Keep It Simple and Consistent.
Presented at: CSML reading group, Department of Statistics, University of Oxford, Oxford, United Kingdom.
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W
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Williamson, RS;
Sahani, M;
Pillow, JW;
(2015)
The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction.
PLOS Computational Biology
, 11
(4)
, Article e1004141. 10.1371/journal.pcbi.1004141.
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