Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Recommendation has become a key feature in the economy of a lot of companies (online shopping, search engines...). There is a lot of work going on regarding recommender systems and there is still a lot to do to improve them. Indeed nowadays in many companies most of the job is done by hand. Moreover even when a supposedly smart recommender system is designed, it is hard to evaluate it without using real audience which obviously involves economic issues. The ICML Exploration & Exploitation challenge is an attempt to make people propose efficient recommendation techniques and particularly focuses on limited computational resources. The challenge also proposes a framework to address the problem of evaluating a recommendation algorithm with real data.  took part in this challenge and achieved the best performances; this paper aims at reporting on this achievement;  also discuss the evaluation process and propose a better one for future challenges of the same kind.
['Olivier Nicol', 'Jérémie Mary', 'Philippe Preux']
I am writing a research paper on a idea ICML exploration & exploitation challenge: keep it simple!
[{"from": "human", "value": "I am writing a research paper on a idea ICML exploration & exploitation challenge: keep it simple!"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Recommendation has become a key feature in the economy of a lot of companies (online shopping, search engines...). There is a lot of work going on regarding recommender systems and there is still a lot to do to improve them. Indeed nowadays in many companies most of the job is done by hand. Moreover even when a supposedly smart recommender system is designed, it is hard to evaluate it without using real audience which obviously involves economic issues. The ICML Exploration & Exploitation challenge is an attempt to make people propose efficient recommendation techniques and particularly focuses on limited computational resources. The challenge also proposes a framework to address the problem of evaluating a recommendation algorithm with real data.  took part in this challenge and achieved the best performances; this paper aims at reporting on this achievement;  also discuss the evaluation process and propose a better one for future challenges of the same kind."}]