Catalytic space enables exact multi-pass algorithms for frequency moments F_k and induced subgraph counting using O(k log m) clean space, while single-pass catalytic algorithms add no power.
Title resolution pending
4 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
4
Pith papers citing it
15
external citations · external index
years
2026 4representative citing papers
Proves the stronger rational-degree conjecture holds with polynomial bounds for monotone, unate, bounded-alternation, symmetric, k-uniform hypergraph, and read-k DNF total Boolean functions.
Deterministic (1+ε)-approximation algorithm for the volume of the unit hypercube truncated by k sums-of-univariate-convex constraints, running in poly_k(n, 1/ε, L, L_o) time.
Three new robust error models for catalytic tape resetting are characterized with equivalences to standard classes and collapse under derandomization.
citing papers explorer
-
Computing over Data Streams using Catalytic Space
Catalytic space enables exact multi-pass algorithms for frequency moments F_k and induced subgraph counting using O(k log m) clean space, while single-pass catalytic algorithms add no power.
-
On the Approximate Non-Deterministic Degree of Total Boolean Functions
Proves the stronger rational-degree conjecture holds with polynomial bounds for monotone, unate, bounded-alternation, symmetric, k-uniform hypergraph, and read-k DNF total Boolean functions.
-
Deterministic Volume Estimation of Truncated Hypercubes
Deterministic (1+ε)-approximation algorithm for the volume of the unit hypercube truncated by k sums-of-univariate-convex constraints, running in poly_k(n, 1/ε, L, L_o) time.
-
Understanding Robust Catalytic Computing
Three new robust error models for catalytic tape resetting are characterized with equivalences to standard classes and collapse under derandomization.