A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
P versus NP and other resource-bounded computation.
Questions regarding well-defined instructions for completing a task, and relevant analysis in terms of time/memory/etc.
Reference-request is used when the author needs to know about work related to the question.
Graph theory is the study of graphs, mathematical structures used to model pairwise relations between objects.
Algorithms on graphs, excluding heuristics.
Questions related to NP-hardness and NP-completeness.
Questions related to combinatorics and discrete mathematical structures
Computational complexity classes and their relations
Computational and mathematical logic.
Questions about approximation algorithms.
formal languages, grammars, automata theory
general questions about selecting a best element from some set of available alternatives.
A soft question is a question (possibly subjective) about the field of theoretical computer science as opposed to being a question in theoretical computer science.
Quantum computation and computational issues related to quantum mechanics
Automata Theory, including abstract machines, grammars, parsing, grammatical inference, transducers, and finite-state techniques
Computability theory a.k.a. recursion theory.
Circuit complexity is the study of resource-bounded circuits and the functions computed by such circuits.
Programming languages, in particular, focussing on their semantics.
Type structure is a syntactic discipline for enforcing levels of abstraction.
Time complexity of decision problems or relations among time-bounded complexity classes. (Use the [analysis-of-algorithms] tag for the time taken by particular algorithms.)
Properties and applications of data structures, such as space lower bounds, or time complexity of insertion and deletion of objects.
Theoretical questions about Machine learning, especially Computational Learning Theory, including Algorithmic Learning Theory, PAC learning, and Bayesian Inference
SAT stands for the Boolean satisfiability problem.
Computational Geometry is the study of geometric problems from a computational perspective. Examples of problems include: computation of geometric objects such as convex hulls, dimensionality reductio…
questions about lowerbounds on functions, usually the complexity of an algorithm or a problem
Theoretical aspects of cryptography and information security.
How hard is counting the number of solutions?
Church's formal system used in computatability, programming languages and proof theory to represent effective functions, programs and their computation, and proofs.
Questions in probability theory
Linear algebra deals with vector spaces and linear transformations.
The Turing machine is a fundamental model of computation, especially in theoretical work.
An algorithm whose behaviour is determined by its input and a generator producing uniformly random numbers.
Questions about Boolean functions and their analysis
Mathematical and computational method for finding the best outcome in a given mathematical model where the list of requirements is represented as linear relationships.
The big picture tag is for a "broad, overall view or perspective of an issue or problem."
Machine learning and learning theory: PAC learning, algorithmic learning theory, and computational aspects of Bayesian inference and graphical models.