Peter Sollich

ORCID

Publication Activity (10 Years)

Years Active: 1994-2022
Publications (10 Years): 9

Top Venues

CoRR

IEEE ACM Trans. Audio Speech Lang. Process.

DSP

J. Mach. Learn. Res.

University of Edinburgh, UK (PHD)

Education History

University of Edinburgh, UK

PHD

Publications

Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
Towards Robust Waveform-Based Acoustic Models. IEEE ACM Trans. Audio Speech Lang. Process. 30 (2022)
Dino Oglic, Zoran Cvetkovic, Peter Sollich
Learning Waveform-Based Acoustic Models Using Deep Variational Convolutional Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 29 (2021)
Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
Towards Robust Waveform-Based Acoustic Models. CoRR (2021)
Edgar Herrera-Delgado, James Briscoe, Peter Sollich
Nonlinear memory functions capture and explain dynamical behaviours. CoRR (2020)
Dino Oglic, Zoran Cvetkovic, Peter Sollich
Parzen Filters for Spectral Decomposition of Signals. CoRR (2019)
Edgar Herrera-Delgado, Ruben Perez-Carrasco, James Briscoe, Peter Sollich
Memory functions reveal structural properties of gene regulatory networks. PLoS Comput. Biol. 14 (2) (2018)
Adriano Barra, Giuseppe Genovese, Daniele Tantari, Peter Sollich
Phase Diagram of Restricted Boltzmann Machines and Generalised Hopfield Networks with Arbitrary Priors. CoRR (2017)
Robin Nicole, Peter Sollich
Dynamical selection of Nash equilibria using Experience Weighted Attraction Learning: emergence of heterogeneous mixed equilibria. CoRR (2017)
Adriano Barra, Giuseppe Genovese, Peter Sollich, Daniele Tantari
Phase transitions in Restricted Boltzmann Machines with generic priors. CoRR (2016)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich, Matthew Ager
A Subband-Based SVM Front-End for Robust ASR. CoRR (2014)
Matthew Ager, Zoran Cvetkovic, Peter Sollich
Phoneme Classification in High-Dimensional Linear Feature Domains. CoRR (2013)
Matthew Urry, Peter Sollich
Random walk kernels and learning curves for Gaussian process regression on random graphs. J. Mach. Learn. Res. 14 (1) (2013)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
Effects of domain-specific SVM kernel design on the robustness of automatic speech recognition. DSP (2013)
Matthew Urry, Peter Sollich
Random walk kernels and learning curves for Gaussian process regression on random graphs CoRR (2012)
Simon R. F. Ashton, Peter Sollich
Learning curves for multi-task Gaussian process regression CoRR (2012)
Peter Sollich, Simon R. F. Ashton
Learning curves for multi-task Gaussian process regression. NIPS (2012)
Matthew Ager, Zoran Cvetkovic, Peter Sollich
Combined waveform-cepstral representation for robust speech recognition. ISIT (2011)
Jibran Yousafzai, Peter Sollich, Zoran Cvetkovic, Bin Yu
Combined Features and Kernel Design for Noise Robust Phoneme Classification Using Support Vector Machines. IEEE Trans. Speech Audio Process. 19 (5) (2011)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
Towards robust phoneme classification with hybrid features. ISIT (2010)
Matthew Urry, Peter Sollich
Exact learning curves for Gaussian process regression on large random graphs. NIPS (2010)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
Subband acoustic waveform front-end for robust speech recognition using support vector machines. SLT (2010)
Matthew Ager, Zoran Cvetkovic, Peter Sollich
High-dimensional linear representations for robust speech recognition. ITA (2010)
Peter Sollich, Matthew Urry, Camille Coti
Kernels and learning curves for Gaussian process regression on random graphs. NIPS (2009)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
Tuning support vector machines for robust phoneme classification with acoustic waveforms. INTERSPEECH (2009)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
Custom-designed SVM kernels for improved robustness of phoneme classification. EUSIPCO (2009)
Matthew Ager, Zoran Cvetkovic, Peter Sollich
Robust phoneme classification: Exploiting the adaptability of acoustic waveform models. EUSIPCO (2009)
Matthew Ager, Zoran Cvetkovic, Peter Sollich, Bin Yu
Towards robust phoneme classification: Augmentation of PLP models with acoustic waveforms. EUSIPCO (2008)
Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich, Bin Yu
Combined PLP - Acoustic waveform classification for robust phoneme recognition using support vector machines. EUSIPCO (2008)
David Barber, Peter Sollich
Stable Belief Propagation in Gaussian Dags. ICASSP (2) (2007)
Nicholas Betteridge, Zoran Cvetkovic, Peter Sollich
Phoneme Classification in Frequency Subbands using Ensemble Methods. DSP (2007)
Lena Khoo, Zoran Cvetkovic, Peter Sollich
Robustness of phoneme classification in different representation spaces. EUSIPCO (2006)
Carl Gold, Alex Holub, Peter Sollich
Bayesian approach to feature selection and parameter tuning for support vector machine classifiers. Neural Networks 18 (5-6) (2005)
Peter Sollich, Christopher K. I. Williams
Understanding Gaussian Process Regression Using the Equivalent Kernel. Deterministic and Statistical Methods in Machine Learning (2004)
Peter Sollich
Can Gaussian Process Regression Be Made Robust Against Model Mismatch? Deterministic and Statistical Methods in Machine Learning (2004)
Peter Sollich, Christopher K. I. Williams
Using the Equivalent Kernel to Understand Gaussian Process Regression. NIPS (2004)
Carl Gold, Peter Sollich
Model selection for support vector machine classification. Neurocomputing 55 (1-2) (2003)
Peter Sollich
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities. Mach. Learn. 46 (1-3) (2002)
Peter Sollich, Anason S. Halees
Learning Curves for Gaussian Process Regression: Approximations and Bounds. Neural Comput. 14 (6) (2002)
Peter Sollich
Gaussian Process Regression with Mismatched Models. NIPS (2001)
Peter Sollich
Probabilistic Methods for Support Vector Machines. NIPS (1999)
David Barber, Peter Sollich
Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks. NIPS (1999)
Peter Sollich, David Barber
Online Learning from Finite Training Sets and Robustness to Input Bias. Neural Comput. 10 (8) (1998)
Peter Sollich
Learning Curves for Gaussian Processes. NIPS (1998)
H. C. Rae, Peter Sollich, Anthony C. C. Coolen
On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories. NIPS (1998)
Peter Sollich, David Barber
On-line Learning from Finite Training Sets in Nonlinear Networks. NIPS (1997)
Peter Sollich, David Barber
Online Learning from Finite Training Sets: An Analytical Case Study. NIPS (1996)
Peter Sollich, Anders Krogh
Learning with ensembles: How overfitting can be useful. NIPS (1995)
Peter Sollich
Minimum entropy queries for linear students learning nonlinear rules. ESANN (1995)
David Barber, David Saad, Peter Sollich
Test Error Fluctuations in Finite Linear Perceptrons. Neural Comput. 7 (4) (1995)
Peter Sollich
Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world. NIPS (1994)
Peter Sollich, David Saad
Learning from queries for maximum information gain in imperfectly learnable problems. NIPS (1994)

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Publication Activity (10 Years)

Top Topics

Top Venues

Peter Sollich