Neil Lawrence – författare

Mainstream brings thirty authors in from the margins to occupy centre-page. Queer storytellers. Working class wordsmiths. Chroniclers of colour. Writers whose life experiences give unique perspectives on universal challenges, whose voices must be heard. And read.‘In these locked down and unfocused times the short story is a much needed respite from the current Covid-19 bleakness. With Mainstream, Inkandescent has gathered together a wonderful collection of fascinating and eclectic stories. Sad, funny, horrifying and demystifying, the unique voices within take us on an open minded journey around the world. Loved it.’ — KATHY BURKE‘A riveting collection of stories, deftly articulated. Every voice entirely captivating: page to page, tale to tale. These are stories told with real heart from writers emerging from the margins in style.’ — ASHLEY HICKSON-LOVENCE, author of The 392 and Your ShowEmerging writers are placed alongside established authors. Contributors are: Aisha Phoenix, Alex Hopkins, Bidisha, Chris Simpson, DJ Connell, Elizabeth Baines, Gaylene Gould, Giselle Leeb, Golnoosh Nour, Hedy Hume, Iqbal Hussain, Jonathan Kemp, Julia Bell, Juliet Jacques, Justin David, Kathy Hoyle, Keith Jarrett, Kerry Hudson, Kit de Waal, Lisa Goldman, Lui Sit, Nathan Evans, Neil Bartlett, Neil Lawrence, Neil McKenna, Ollie Charles, Padrika Tarrant, Paul McVeigh, Philip Ridley, Polis Loizou.

Machinelearningis arapidlymaturing?eldthataims toprovidepracticalme- ods for data discovery, categorization and modelling. The She?eld Machine Learning Workshop, which was held 7-10 September 2004, brought together some of the leading international researchers in the ?eld for a series of talks and posters that represented new developments in machine learning and numerical methods. The workshop was sponsored by the Engineering and Physical Sciences - search Council (EPSRC) and the London Mathematical Society (LMS) through the MathFIT program,whose aim is the encouragementof new interdisciplinary research.AdditionalfundingwasprovidedbythePASCALEuropeanFramework 6 Network of Excellence and the University of She?eld. It was the commitment of these funding bodies that enabled the workshop to have a strong program of invited speakers,and the organizerswish to thank these funding bodies for their ?nancial support. The particular focus for interactions at the workshop was - vanced Research Methods in Machine Learning and Statistical Signal Processing.These proceedings contain work that was presented at the workshop, and ideas that were developed through, or inspired by, attendance at the workshop. The proceedings re?ect this mixture and illustrate the diversity of applications and theoretical work in machine learning. We would like to thank the presenters and attendees at the workshop for the excellent quality of presentation and discussion during the oral and poster sessions. We are also grateful to Gillian Callaghan for her support in the orga- zation of the workshop, and ?nally we wish to thank the anonymous reviewers for their help in compiling the proceedings.