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Electronic Colloquium on Computational Complexity

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REPORTS > AUTHORS > TONIANN PITASSI:
All reports by Author Toniann Pitassi:

TR26-312 | 5th November 2026
Clement Canonne, Xi Chen, William Pires, Toniann Pitassi, Rocco Servedio

The Space Complexity of Property Testing

We initiate the study of the space complexity of property testing. We focus on five properties of Boolean functions that have been intensively studied in the property testing literature: monotonicity, symmetry, linearity, being a junta, and being a linear threshold function.

On the upper bounds side, we show --- ... more >>>


TR26-109 | 26th June 2026
Noah Fleming, Stefan Grosser, Toniann Pitassi, Robert Robere

Provable Reductions in TFNP

We introduce a new family of propositional proof systems, denoted $\langle EF, R \rangle$, for an arbitrary TFNP search problem $R$. Informally, a refutation of a CNF formula $F$ in $\langle EF, R \rangle$ is given by a polynomial-time mapping reduction from the false-clause search problem ${\mathrm{Search}}_F$ to $R$, combined ... more >>>


TR25-030 | 15th March 2025
Oliver Korten, Toniann Pitassi, Russell Impagliazzo

Stronger Cell Probe Lower Bounds via Local PRGs

Revisions: 1

In this work we observe a tight connection between three topics: $NC^0$ cryptography, $NC^0$ range avoidance, and static data structure lower bounds. Using this connection, we leverage techniques from the cryptanalysis of $NC^0$ PRGs to prove state-of-the-art results in the latter two subjects. Our main result is a quadratic improvement ... more >>>


TR24-205 | 17th December 2024
Tsun-Ming Cheung, Hamed Hatami, Kaave Hosseini, Aleksandar Nikolov, Toniann Pitassi, Morgan Shirley

A Lower Bound on the Trace Norm of Boolean Matrices and its Applications

We present a simple method based on a variant of Hölder's inequality to lower-bound the trace norm of Boolean matrices. As the main result, we obtain an exponential separation between the randomized decision tree depth and the spectral norm (i.e. the Fourier $L_1$-norm) of a Boolean function. This answers an ... more >>>




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