AbstractA Boolean function f(x1,…,xn) is elusive if every decision tree evaluating f must examine all n variables in the worst case. Rivest and Vuillemin conjectured that every nontrivial monotone weakly symmetric Boolean function is elusive. In this note, we show that this conjecture is true for n = 6
AbstractRecently, Keller and Pilpel conjectured that the influence of a monotone Boolean function do...
AbstractIn this paper, we present the empirical results for relationships between time (depth) and s...
AbstractWe study the learnability of boolean functions from membership and equivalence queries. We d...
AbstractA Boolean function f(x1,…,xn) is elusive if every decision tree evaluating f must examine al...
AbstractA Boolean function f(x1,x2,…,xn) is elusive if every decision tree computing f must examine ...
AbstractA Boolean function f(x1, …, xn) is elusive if every decision tree evaluating f must examine ...
A Boolean function f(x1, x2, …, xn) is elusive if every decision tree computing f must examine all ...
AbstractA Boolean function f(x1, …, xn) is elusive if every decision tree evaluating f must examine ...
AbstractIn this paper, we present the empirical results for relationships between time (depth) and s...
© 2014 Elsevier B.V. For a Boolean function f, let D(f) denote its deterministic decision tree compl...
This thesis focuses on finding counterexamples for the conjecture suggested by Dr. Jackson that if t...
A Boolean function on $N$ variables is called emph{evasive} if its decision-tree complexity is $N$. ...
A longstanding lacuna in the field of computational learning theory is the learnability of succinctl...
We give an algorithm that learns any monotone Boolean function f: {−1, 1}n → {−1, 1} to any constant...
We study the learnability of boolean functions from membership and equivalence queries. We develop t...
AbstractRecently, Keller and Pilpel conjectured that the influence of a monotone Boolean function do...
AbstractIn this paper, we present the empirical results for relationships between time (depth) and s...
AbstractWe study the learnability of boolean functions from membership and equivalence queries. We d...
AbstractA Boolean function f(x1,…,xn) is elusive if every decision tree evaluating f must examine al...
AbstractA Boolean function f(x1,x2,…,xn) is elusive if every decision tree computing f must examine ...
AbstractA Boolean function f(x1, …, xn) is elusive if every decision tree evaluating f must examine ...
A Boolean function f(x1, x2, …, xn) is elusive if every decision tree computing f must examine all ...
AbstractA Boolean function f(x1, …, xn) is elusive if every decision tree evaluating f must examine ...
AbstractIn this paper, we present the empirical results for relationships between time (depth) and s...
© 2014 Elsevier B.V. For a Boolean function f, let D(f) denote its deterministic decision tree compl...
This thesis focuses on finding counterexamples for the conjecture suggested by Dr. Jackson that if t...
A Boolean function on $N$ variables is called emph{evasive} if its decision-tree complexity is $N$. ...
A longstanding lacuna in the field of computational learning theory is the learnability of succinctl...
We give an algorithm that learns any monotone Boolean function f: {−1, 1}n → {−1, 1} to any constant...
We study the learnability of boolean functions from membership and equivalence queries. We develop t...
AbstractRecently, Keller and Pilpel conjectured that the influence of a monotone Boolean function do...
AbstractIn this paper, we present the empirical results for relationships between time (depth) and s...
AbstractWe study the learnability of boolean functions from membership and equivalence queries. We d...