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Found 7 papers, 0 papers with code
On the tightness of linear relaxation based robustness certification methods
There has been a rapid development and interest in adversarial training and defenses in the machine learning community in the recent years.
Neural document expansion for ad-hoc information retrieval
Recently, Nogueira et al. [2019] proposed a new approach to document expansion based on a neural Seq2Seq model, showing significant improvement on short text retrieval task.
Exponentially convergent stochastic k-PCA without variance reduction
We present Matrix Krasulina, an algorithm for online k-PCA, by generalizing the classic Krasulina's method (Krasulina, 1969) from vector to matrix case.
When do random forests fail?
As a consequence, even highly randomized trees can lead to inconsistent forests if no subsampling is used, which implies that some of the commonly used setups for random forests can be inconsistent.
Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization
Auto-encoders are commonly used for unsupervised representation learning and for pre-training deeper neural networks.
Convergence rate of stochastic k-means
We analyze online \cite{BottouBengio} and mini-batch \cite{Sculley} $k$-means variants.
