93 citations · 364 across the 34 of their papers we have counts for
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Optimal Binary Classifier Aggregation for General Losses
Akshay Balsubramani, Yoav Freund
We address the problem of aggregating an ensemble of predictors with known loss bounds in a semi-supervised binary classification setting, to minimize prediction loss incurred on t…
Scalable Semi-Supervised Aggregation of Classifiers
Akshay Balsubramani, Yoav Freund
We present and empirically evaluate an efficient algorithm that learns to aggregate the predictions of an ensemble of binary classifiers. The algorithm uses the structure of the en…
Optimally Combining Classifiers Using Unlabeled Data
Akshay Balsubramani, Yoav Freund
We develop a worst-case analysis of aggregation of classifier ensembles for binary classification. The task of predicting to minimize error is formulated as a game played over a gi…
PAC-Bayes with Minimax for Confidence-Rated Transduction
Akshay Balsubramani, Yoav Freund
We consider using an ensemble of binary classifiers for transductive prediction, when unlabeled test data are known in advance. We derive minimax optimal rules for confidence-rated…
The Fast Convergence of Incremental PCA
Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund
We consider a situation in which we see samples in drawn i.i.d. from some distribution with mean zero and unknown covariance A. We wish to compute the top eigenvecto…