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Introduction: The ICML paper deadline has passed. Joelle and I were surprised to see the number of submissions jump from last year by about 50% to around 900 submissions. A tiny portion of these are immediate rejects(*), so this is a much larger set of papers than expected. The number of workshop submissions also doubled compared to last year, so ICML may grow significantly this year, if we can manage to handle the load well. The prospect of making 900 good decisions is fundamentally daunting, and success will rely heavily on the program committee and area chairs at this point. For those who want to rubberneck a bit more, here’s a breakdown of submissions by primary topic of submitted papers: 66 Reinforcement Learning 52 Supervised Learning 51 Clustering 46 Kernel Methods 40 Optimization Algorithms 39 Feature Selection and Dimensionality Reduction 33 Learning Theory 33 Graphical Models 33 Applications 29 Probabilistic Models 29 NN & Deep Learning 26 Transfer and Multi-Ta


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1 Joelle and I were surprised to see the number of submissions jump from last year by about 50% to around 900 submissions. [sent-2, score-0.417]

2 A tiny portion of these are immediate rejects(*), so this is a much larger set of papers than expected. [sent-3, score-0.168]

3 The number of workshop submissions also doubled compared to last year, so ICML may grow significantly this year, if we can manage to handle the load well. [sent-4, score-0.341]

4 The prospect of making 900 good decisions is fundamentally daunting, and success will rely heavily on the program committee and area chairs at this point. [sent-5, score-0.099]

5 But, they have to be real deadlines to achieve this, which leads us to reject late submissions & format failures to keep the deadline real for future ICMLs. [sent-7, score-0.556]


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Introduction: The ICML paper deadline has passed. Joelle and I were surprised to see the number of submissions jump from last year by about 50% to around 900 submissions. A tiny portion of these are immediate rejects(*), so this is a much larger set of papers than expected. The number of workshop submissions also doubled compared to last year, so ICML may grow significantly this year, if we can manage to handle the load well. The prospect of making 900 good decisions is fundamentally daunting, and success will rely heavily on the program committee and area chairs at this point. For those who want to rubberneck a bit more, here’s a breakdown of submissions by primary topic of submitted papers: 66 Reinforcement Learning 52 Supervised Learning 51 Clustering 46 Kernel Methods 40 Optimization Algorithms 39 Feature Selection and Dimensionality Reduction 33 Learning Theory 33 Graphical Models 33 Applications 29 Probabilistic Models 29 NN & Deep Learning 26 Transfer and Multi-Ta

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